parent
d02f55ae0b
commit
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17 changed files with 6469 additions and 0 deletions
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import numpy as np |
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import math |
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|
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from selfdrive.swaglog import cloudlog |
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from common.realtime import sec_since_boot |
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from selfdrive.controls.lib.longitudinal_mpc_model import libmpc_py |
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class LongitudinalMpcModel(): |
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def __init__(self): |
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self.setup_mpc() |
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self.v_mpc = 0.0 |
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self.v_mpc_future = 0.0 |
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self.a_mpc = 0.0 |
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self.last_cloudlog_t = 0.0 |
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self.ts = list(range(10)) |
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self.valid = False |
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def setup_mpc(self, v_ego=0.0): |
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self.libmpc = libmpc_py.libmpc |
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self.libmpc.init(1.0, 1.0, 1.0, 1.0, 1.0) |
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self.libmpc.init_with_simulation(v_ego) |
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self.mpc_solution = libmpc_py.ffi.new("log_t *") |
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self.cur_state = libmpc_py.ffi.new("state_t *") |
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self.cur_state[0].x_ego = 0 |
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self.cur_state[0].v_ego = 0 |
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self.cur_state[0].a_ego = 0 |
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def set_cur_state(self, v, a): |
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self.cur_state[0].x_ego = 0.0 |
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self.cur_state[0].v_ego = v |
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self.cur_state[0].a_ego = a |
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def update(self, CS, model): |
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v_ego = CS.vEgo |
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longitudinal = model.longitudinal |
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if len(longitudinal.distances) == 0: |
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self.valid = False |
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return |
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x_poly = list(map(float, np.polyfit(self.ts, longitudinal.distances, 3))) |
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v_poly = list(map(float, np.polyfit(self.ts, longitudinal.speeds, 3))) |
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a_poly = list(map(float, np.polyfit(self.ts, longitudinal.accelerations, 3))) |
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# Calculate mpc |
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self.libmpc.run_mpc(self.cur_state, self.mpc_solution, x_poly, v_poly, a_poly) |
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# Get solution. MPC timestep is 0.2 s, so interpolation to 0.05 s is needed |
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self.v_mpc = self.mpc_solution[0].v_ego[1] |
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self.a_mpc = self.mpc_solution[0].a_ego[1] |
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self.v_mpc_future = self.mpc_solution[0].v_ego[10] |
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self.valid = True |
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# Reset if NaN or goes through lead car |
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nans = any(math.isnan(x) for x in self.mpc_solution[0].v_ego) |
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t = sec_since_boot() |
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if nans: |
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if t > self.last_cloudlog_t + 5.0: |
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self.last_cloudlog_t = t |
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cloudlog.warning("Longitudinal model mpc reset - backwards") |
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self.libmpc.init(1.0, 1.0, 1.0, 1.0, 1.0) |
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self.libmpc.init_with_simulation(v_ego) |
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self.cur_state[0].v_ego = v_ego |
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self.cur_state[0].a_ego = 0.0 |
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self.v_mpc = v_ego |
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self.a_mpc = CS.aEgo |
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self.valid = False |
@ -0,0 +1,2 @@ |
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generator |
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lib_qp/ |
@ -0,0 +1,31 @@ |
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Import('env', 'arch') |
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cpp_path = [ |
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"#phonelibs/acado/include", |
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"#phonelibs/acado/include/acado", |
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"#phonelibs/qpoases/INCLUDE", |
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"#phonelibs/qpoases/INCLUDE/EXTRAS", |
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"#phonelibs/qpoases/SRC/", |
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"#phonelibs/qpoases", |
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"lib_mpc_export" |
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] |
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mpc_files = [ |
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"longitudinal_mpc.c", |
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Glob("lib_mpc_export/*.c"), |
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Glob("lib_mpc_export/*.cpp"), |
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] |
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interface_dir = Dir('lib_mpc_export') |
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SConscript(['#phonelibs/qpoases/SConscript'], variant_dir='lib_qp', exports=['interface_dir']) |
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env.SharedLibrary('mpc', mpc_files, LIBS=['m', 'qpoases'], LIBPATH=['lib_qp'], CPPPATH=cpp_path) |
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# if arch != "aarch64": |
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# acado_libs = [File("#phonelibs/acado/x64/lib/libacado_toolkit.a"), |
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# File("#phonelibs/acado/x64/lib/libacado_casadi.a"), |
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# File("#phonelibs/acado/x64/lib/libacado_csparse.a")] |
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# env.Program('generator', 'generator.cpp', LIBS=acado_libs, CPPPATH=cpp_path) |
@ -0,0 +1,99 @@ |
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#include <acado_code_generation.hpp> |
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const int controlHorizon = 50; |
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using namespace std; |
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int main( ) |
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{ |
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USING_NAMESPACE_ACADO |
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DifferentialEquation f; |
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DifferentialState x_ego, v_ego, a_ego, t; |
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OnlineData x_poly_r0, x_poly_r1, x_poly_r2, x_poly_r3; |
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OnlineData v_poly_r0, v_poly_r1, v_poly_r2, v_poly_r3; |
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OnlineData a_poly_r0, a_poly_r1, a_poly_r2, a_poly_r3; |
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Control j_ego; |
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// Equations of motion
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f << dot(x_ego) == v_ego; |
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f << dot(v_ego) == a_ego; |
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f << dot(a_ego) == j_ego; |
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f << dot(t) == 1; |
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auto poly_x = x_poly_r0*(t*t*t) + x_poly_r1*(t*t) + x_poly_r2*t + x_poly_r3; |
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auto poly_v = v_poly_r0*(t*t*t) + v_poly_r1*(t*t) + v_poly_r2*t + v_poly_r3; |
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auto poly_a = a_poly_r0*(t*t*t) + a_poly_r1*(t*t) + a_poly_r2*t + a_poly_r3; |
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|
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// Running cost
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Function h; |
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h << x_ego - poly_x; |
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h << v_ego - poly_v; |
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h << a_ego - poly_a; |
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h << a_ego * (0.1 * v_ego + 1.0); |
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h << j_ego * (0.1 * v_ego + 1.0); |
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// Weights are defined in mpc.
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BMatrix Q(5,5); Q.setAll(true); |
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// Terminal cost
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Function hN; |
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hN << x_ego - poly_x; |
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hN << v_ego - poly_v; |
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hN << a_ego - poly_a; |
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hN << a_ego * (0.1 * v_ego + 1.0); |
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// Weights are defined in mpc.
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BMatrix QN(4,4); QN.setAll(true); |
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// Non uniform time grid
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// First 5 timesteps are 0.2, after that it's 0.6
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DMatrix numSteps(20, 1); |
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for (int i = 0; i < 5; i++){ |
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numSteps(i) = 1; |
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} |
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for (int i = 5; i < 20; i++){ |
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numSteps(i) = 3; |
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} |
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// Setup Optimal Control Problem
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const double tStart = 0.0; |
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const double tEnd = 10.0; |
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OCP ocp( tStart, tEnd, numSteps); |
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ocp.subjectTo(f); |
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ocp.minimizeLSQ(Q, h); |
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ocp.minimizeLSQEndTerm(QN, hN); |
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//ocp.subjectTo( 0.0 <= v_ego);
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ocp.setNOD(12); |
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OCPexport mpc(ocp); |
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mpc.set( HESSIAN_APPROXIMATION, GAUSS_NEWTON ); |
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mpc.set( DISCRETIZATION_TYPE, MULTIPLE_SHOOTING ); |
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mpc.set( INTEGRATOR_TYPE, INT_RK4 ); |
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mpc.set( NUM_INTEGRATOR_STEPS, controlHorizon); |
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mpc.set( MAX_NUM_QP_ITERATIONS, 500); |
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mpc.set( CG_USE_VARIABLE_WEIGHTING_MATRIX, YES); |
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mpc.set( SPARSE_QP_SOLUTION, CONDENSING ); |
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mpc.set( QP_SOLVER, QP_QPOASES ); |
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mpc.set( HOTSTART_QP, YES ); |
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mpc.set( GENERATE_TEST_FILE, NO); |
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mpc.set( GENERATE_MAKE_FILE, NO ); |
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mpc.set( GENERATE_MATLAB_INTERFACE, NO ); |
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mpc.set( GENERATE_SIMULINK_INTERFACE, NO ); |
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if (mpc.exportCode( "lib_mpc_export" ) != SUCCESSFUL_RETURN) |
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exit( EXIT_FAILURE ); |
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mpc.printDimensionsQP( ); |
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return EXIT_SUCCESS; |
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} |
@ -0,0 +1,212 @@ |
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/*
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* This file was auto-generated using the ACADO Toolkit. |
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*
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* While ACADO Toolkit is free software released under the terms of |
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* the GNU Lesser General Public License (LGPL), the generated code |
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* as such remains the property of the user who used ACADO Toolkit |
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* to generate this code. In particular, user dependent data of the code |
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* do not inherit the GNU LGPL license. On the other hand, parts of the |
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* generated code that are a direct copy of source code from the |
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* ACADO Toolkit or the software tools it is based on, remain, as derived |
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* work, automatically covered by the LGPL license. |
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*
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* ACADO Toolkit is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
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*
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*/ |
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#include "acado_auxiliary_functions.h" |
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#include <stdio.h> |
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real_t* acado_getVariablesX( ) |
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{ |
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return acadoVariables.x; |
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} |
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real_t* acado_getVariablesU( ) |
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{ |
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return acadoVariables.u; |
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} |
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#if ACADO_NY > 0 |
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real_t* acado_getVariablesY( ) |
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{ |
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return acadoVariables.y; |
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} |
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#endif |
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#if ACADO_NYN > 0 |
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real_t* acado_getVariablesYN( ) |
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{ |
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return acadoVariables.yN; |
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} |
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#endif |
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real_t* acado_getVariablesX0( ) |
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{ |
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#if ACADO_INITIAL_VALUE_FIXED |
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return acadoVariables.x0; |
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#else |
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return 0; |
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#endif |
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} |
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/** Print differential variables. */ |
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void acado_printDifferentialVariables( ) |
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{ |
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int i, j; |
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printf("\nDifferential variables:\n[\n"); |
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for (i = 0; i < ACADO_N + 1; ++i) |
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{ |
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for (j = 0; j < ACADO_NX; ++j) |
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printf("\t%e", acadoVariables.x[i * ACADO_NX + j]); |
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printf("\n"); |
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} |
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printf("]\n\n"); |
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} |
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/** Print control variables. */ |
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void acado_printControlVariables( ) |
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{ |
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int i, j; |
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printf("\nControl variables:\n[\n"); |
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for (i = 0; i < ACADO_N; ++i) |
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{ |
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for (j = 0; j < ACADO_NU; ++j) |
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printf("\t%e", acadoVariables.u[i * ACADO_NU + j]); |
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printf("\n"); |
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} |
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printf("]\n\n"); |
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} |
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/** Print ACADO code generation notice. */ |
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void acado_printHeader( ) |
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{ |
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printf( |
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"\nACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.\n" |
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"Copyright (C) 2008-2015 by Boris Houska, Hans Joachim Ferreau,\n"
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"Milan Vukov and Rien Quirynen, KU Leuven.\n" |
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); |
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printf( |
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"Developed within the Optimization in Engineering Center (OPTEC) under\n" |
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"supervision of Moritz Diehl. All rights reserved.\n\n" |
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"ACADO Toolkit is distributed under the terms of the GNU Lesser\n" |
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"General Public License 3 in the hope that it will be useful,\n" |
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"but WITHOUT ANY WARRANTY; without even the implied warranty of\n" |
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"MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n" |
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"GNU Lesser General Public License for more details.\n\n" |
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); |
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} |
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#if !(defined _DSPACE) |
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#if (defined _WIN32 || defined _WIN64) && !(defined __MINGW32__ || defined __MINGW64__) |
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void acado_tic( acado_timer* t ) |
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{ |
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QueryPerformanceFrequency(&t->freq); |
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QueryPerformanceCounter(&t->tic); |
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} |
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real_t acado_toc( acado_timer* t ) |
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{ |
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QueryPerformanceCounter(&t->toc); |
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return ((t->toc.QuadPart - t->tic.QuadPart) / (real_t)t->freq.QuadPart); |
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} |
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#elif (defined __APPLE__) |
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void acado_tic( acado_timer* t ) |
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{ |
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/* read current clock cycles */ |
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t->tic = mach_absolute_time(); |
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} |
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real_t acado_toc( acado_timer* t ) |
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{ |
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uint64_t duration; /* elapsed time in clock cycles*/ |
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t->toc = mach_absolute_time(); |
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duration = t->toc - t->tic; |
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/*conversion from clock cycles to nanoseconds*/ |
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mach_timebase_info(&(t->tinfo)); |
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duration *= t->tinfo.numer; |
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duration /= t->tinfo.denom; |
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return (real_t)duration / 1e9; |
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} |
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#else |
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#if __STDC_VERSION__ >= 199901L |
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/* C99 mode */ |
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/* read current time */ |
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void acado_tic( acado_timer* t ) |
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{ |
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gettimeofday(&t->tic, 0); |
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} |
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/* return time passed since last call to tic on this timer */ |
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real_t acado_toc( acado_timer* t ) |
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{ |
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struct timeval temp; |
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gettimeofday(&t->toc, 0); |
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if ((t->toc.tv_usec - t->tic.tv_usec) < 0) |
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{ |
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temp.tv_sec = t->toc.tv_sec - t->tic.tv_sec - 1; |
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temp.tv_usec = 1000000 + t->toc.tv_usec - t->tic.tv_usec; |
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} |
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else |
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{ |
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temp.tv_sec = t->toc.tv_sec - t->tic.tv_sec; |
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temp.tv_usec = t->toc.tv_usec - t->tic.tv_usec; |
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} |
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return (real_t)temp.tv_sec + (real_t)temp.tv_usec / 1e6; |
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} |
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#else |
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/* ANSI */ |
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/* read current time */ |
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void acado_tic( acado_timer* t ) |
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{ |
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clock_gettime(CLOCK_MONOTONIC, &t->tic); |
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} |
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|
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/* return time passed since last call to tic on this timer */ |
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real_t acado_toc( acado_timer* t ) |
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{ |
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struct timespec temp; |
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clock_gettime(CLOCK_MONOTONIC, &t->toc);
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if ((t->toc.tv_nsec - t->tic.tv_nsec) < 0) |
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{ |
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temp.tv_sec = t->toc.tv_sec - t->tic.tv_sec - 1; |
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temp.tv_nsec = 1000000000+t->toc.tv_nsec - t->tic.tv_nsec; |
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} |
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else |
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{ |
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temp.tv_sec = t->toc.tv_sec - t->tic.tv_sec; |
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temp.tv_nsec = t->toc.tv_nsec - t->tic.tv_nsec; |
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} |
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return (real_t)temp.tv_sec + (real_t)temp.tv_nsec / 1e9; |
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} |
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#endif /* __STDC_VERSION__ >= 199901L */ |
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#endif /* (defined _WIN32 || _WIN64) */ |
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#endif |
@ -0,0 +1,138 @@ |
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/*
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* This file was auto-generated using the ACADO Toolkit. |
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*
|
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* While ACADO Toolkit is free software released under the terms of |
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* the GNU Lesser General Public License (LGPL), the generated code |
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* as such remains the property of the user who used ACADO Toolkit |
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* to generate this code. In particular, user dependent data of the code |
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* do not inherit the GNU LGPL license. On the other hand, parts of the |
||||
* generated code that are a direct copy of source code from the |
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* ACADO Toolkit or the software tools it is based on, remain, as derived |
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* work, automatically covered by the LGPL license. |
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*
|
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* ACADO Toolkit is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
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*
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*/ |
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#ifndef ACADO_AUXILIARY_FUNCTIONS_H |
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#define ACADO_AUXILIARY_FUNCTIONS_H |
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#include "acado_common.h" |
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#ifndef __MATLAB__ |
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#ifdef __cplusplus |
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extern "C" |
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{ |
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#endif /* __cplusplus */ |
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#endif /* __MATLAB__ */ |
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/** Get pointer to the matrix with differential variables. */ |
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real_t* acado_getVariablesX( ); |
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/** Get pointer to the matrix with control variables. */ |
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real_t* acado_getVariablesU( ); |
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#if ACADO_NY > 0 |
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/** Get pointer to the matrix with references/measurements. */ |
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real_t* acado_getVariablesY( ); |
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#endif |
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#if ACADO_NYN > 0 |
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/** Get pointer to the vector with references/measurement on the last node. */ |
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real_t* acado_getVariablesYN( ); |
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#endif |
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|
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/** Get pointer to the current state feedback vector. Only applicable for NMPC. */ |
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real_t* acado_getVariablesX0( ); |
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/** Print differential variables. */ |
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void acado_printDifferentialVariables( ); |
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/** Print control variables. */ |
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void acado_printControlVariables( ); |
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|
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/** Print ACADO code generation notice. */ |
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void acado_printHeader( ); |
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/*
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* A huge thanks goes to Alexander Domahidi from ETHZ, Switzerland, for
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* providing us with the following timing routines. |
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*/ |
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#if !(defined _DSPACE) |
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#if (defined _WIN32 || defined _WIN64) && !(defined __MINGW32__ || defined __MINGW64__) |
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/* Use Windows QueryPerformanceCounter for timing. */ |
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#include <Windows.h> |
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/** A structure for keeping internal timer data. */ |
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typedef struct acado_timer_ |
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{ |
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LARGE_INTEGER tic; |
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LARGE_INTEGER toc; |
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LARGE_INTEGER freq; |
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} acado_timer; |
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#elif (defined __APPLE__) |
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#include "unistd.h" |
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#include <mach/mach_time.h> |
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/** A structure for keeping internal timer data. */ |
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typedef struct acado_timer_ |
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{ |
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uint64_t tic; |
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uint64_t toc; |
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mach_timebase_info_data_t tinfo; |
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} acado_timer; |
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#else |
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/* Use POSIX clock_gettime() for timing on non-Windows machines. */ |
||||
#include <time.h> |
||||
|
||||
#if __STDC_VERSION__ >= 199901L |
||||
/* C99 mode of operation. */ |
||||
|
||||
#include <sys/stat.h> |
||||
#include <sys/time.h> |
||||
|
||||
typedef struct acado_timer_ |
||||
{ |
||||
struct timeval tic; |
||||
struct timeval toc; |
||||
} acado_timer; |
||||
|
||||
#else |
||||
/* ANSI C */ |
||||
|
||||
/** A structure for keeping internal timer data. */ |
||||
typedef struct acado_timer_ |
||||
{ |
||||
struct timespec tic; |
||||
struct timespec toc; |
||||
} acado_timer; |
||||
|
||||
#endif /* __STDC_VERSION__ >= 199901L */ |
||||
|
||||
#endif /* (defined _WIN32 || defined _WIN64) */ |
||||
|
||||
/** A function for measurement of the current time. */ |
||||
void acado_tic( acado_timer* t ); |
||||
|
||||
/** A function which returns the elapsed time. */ |
||||
real_t acado_toc( acado_timer* t ); |
||||
|
||||
#endif |
||||
|
||||
#ifndef __MATLAB__ |
||||
#ifdef __cplusplus |
||||
} /* extern "C" */ |
||||
#endif /* __cplusplus */ |
||||
#endif /* __MATLAB__ */ |
||||
|
||||
#endif /* ACADO_AUXILIARY_FUNCTIONS_H */ |
@ -0,0 +1,342 @@ |
||||
/*
|
||||
* This file was auto-generated using the ACADO Toolkit. |
||||
*
|
||||
* While ACADO Toolkit is free software released under the terms of |
||||
* the GNU Lesser General Public License (LGPL), the generated code |
||||
* as such remains the property of the user who used ACADO Toolkit |
||||
* to generate this code. In particular, user dependent data of the code |
||||
* do not inherit the GNU LGPL license. On the other hand, parts of the |
||||
* generated code that are a direct copy of source code from the |
||||
* ACADO Toolkit or the software tools it is based on, remain, as derived |
||||
* work, automatically covered by the LGPL license. |
||||
*
|
||||
* ACADO Toolkit is distributed in the hope that it will be useful, |
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of |
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
||||
*
|
||||
*/ |
||||
|
||||
|
||||
#ifndef ACADO_COMMON_H |
||||
#define ACADO_COMMON_H |
||||
|
||||
#include <math.h> |
||||
#include <string.h> |
||||
|
||||
#ifndef __MATLAB__ |
||||
#ifdef __cplusplus |
||||
extern "C" |
||||
{ |
||||
#endif /* __cplusplus */ |
||||
#endif /* __MATLAB__ */ |
||||
|
||||
/** \defgroup ACADO ACADO CGT generated module. */ |
||||
/** @{ */ |
||||
|
||||
/** qpOASES QP solver indicator. */ |
||||
#define ACADO_QPOASES 0 |
||||
#define ACADO_QPOASES3 1 |
||||
/** FORCES QP solver indicator.*/ |
||||
#define ACADO_FORCES 2 |
||||
/** qpDUNES QP solver indicator.*/ |
||||
#define ACADO_QPDUNES 3 |
||||
/** HPMPC QP solver indicator. */ |
||||
#define ACADO_HPMPC 4 |
||||
#define ACADO_GENERIC 5 |
||||
|
||||
/** Indicator for determining the QP solver used by the ACADO solver code. */ |
||||
#define ACADO_QP_SOLVER ACADO_QPOASES |
||||
|
||||
#include "acado_qpoases_interface.hpp" |
||||
|
||||
|
||||
/*
|
||||
* Common definitions |
||||
*/ |
||||
/** User defined block based condensing. */ |
||||
#define ACADO_BLOCK_CONDENSING 0 |
||||
/** Compute covariance matrix of the last state estimate. */ |
||||
#define ACADO_COMPUTE_COVARIANCE_MATRIX 0 |
||||
/** Flag indicating whether constraint values are hard-coded or not. */ |
||||
#define ACADO_HARDCODED_CONSTRAINT_VALUES 1 |
||||
/** Indicator for fixed initial state. */ |
||||
#define ACADO_INITIAL_STATE_FIXED 1 |
||||
/** Number of control/estimation intervals. */ |
||||
#define ACADO_N 20 |
||||
/** Number of online data values. */ |
||||
#define ACADO_NOD 12 |
||||
/** Number of path constraints. */ |
||||
#define ACADO_NPAC 0 |
||||
/** Number of control variables. */ |
||||
#define ACADO_NU 1 |
||||
/** Number of differential variables. */ |
||||
#define ACADO_NX 4 |
||||
/** Number of algebraic variables. */ |
||||
#define ACADO_NXA 0 |
||||
/** Number of differential derivative variables. */ |
||||
#define ACADO_NXD 0 |
||||
/** Number of references/measurements per node on the first N nodes. */ |
||||
#define ACADO_NY 5 |
||||
/** Number of references/measurements on the last (N + 1)st node. */ |
||||
#define ACADO_NYN 4 |
||||
/** Total number of QP optimization variables. */ |
||||
#define ACADO_QP_NV 24 |
||||
/** Number of Runge-Kutta stages per integration step. */ |
||||
#define ACADO_RK_NSTAGES 4 |
||||
/** Providing interface for arrival cost. */ |
||||
#define ACADO_USE_ARRIVAL_COST 0 |
||||
/** Indicator for usage of non-hard-coded linear terms in the objective. */ |
||||
#define ACADO_USE_LINEAR_TERMS 0 |
||||
/** Indicator for type of fixed weighting matrices. */ |
||||
#define ACADO_WEIGHTING_MATRICES_TYPE 2 |
||||
|
||||
|
||||
/*
|
||||
* Globally used structure definitions |
||||
*/ |
||||
|
||||
/** The structure containing the user data.
|
||||
*
|
||||
* Via this structure the user "communicates" with the solver code. |
||||
*/ |
||||
typedef struct ACADOvariables_ |
||||
{ |
||||
int dummy; |
||||
/** Matrix of size: 21 x 4 (row major format)
|
||||
*
|
||||
* Matrix containing 21 differential variable vectors. |
||||
*/ |
||||
real_t x[ 84 ]; |
||||
|
||||
/** Column vector of size: 20
|
||||
*
|
||||
* Matrix containing 20 control variable vectors. |
||||
*/ |
||||
real_t u[ 20 ]; |
||||
|
||||
/** Matrix of size: 21 x 12 (row major format)
|
||||
*
|
||||
* Matrix containing 21 online data vectors. |
||||
*/ |
||||
real_t od[ 252 ]; |
||||
|
||||
/** Column vector of size: 100
|
||||
*
|
||||
* Matrix containing 20 reference/measurement vectors of size 5 for first 20 nodes. |
||||
*/ |
||||
real_t y[ 100 ]; |
||||
|
||||
/** Column vector of size: 4
|
||||
*
|
||||
* Reference/measurement vector for the 21. node. |
||||
*/ |
||||
real_t yN[ 4 ]; |
||||
|
||||
/** Matrix of size: 100 x 5 (row major format) */ |
||||
real_t W[ 500 ]; |
||||
|
||||
/** Matrix of size: 4 x 4 (row major format) */ |
||||
real_t WN[ 16 ]; |
||||
|
||||
/** Column vector of size: 4
|
||||
*
|
||||
* Current state feedback vector. |
||||
*/ |
||||
real_t x0[ 4 ]; |
||||
|
||||
|
||||
} ACADOvariables; |
||||
|
||||
/** Private workspace used by the auto-generated code.
|
||||
*
|
||||
* Data members of this structure are private to the solver. |
||||
* In other words, the user code should not modify values of this
|
||||
* structure.
|
||||
*/ |
||||
typedef struct ACADOworkspace_ |
||||
{ |
||||
real_t rk_ttt; |
||||
|
||||
/** Row vector of size: 37 */ |
||||
real_t rk_xxx[ 37 ]; |
||||
|
||||
/** Matrix of size: 4 x 24 (row major format) */ |
||||
real_t rk_kkk[ 96 ]; |
||||
|
||||
/** Row vector of size: 37 */ |
||||
real_t state[ 37 ]; |
||||
|
||||
/** Column vector of size: 80 */ |
||||
real_t d[ 80 ]; |
||||
|
||||
/** Column vector of size: 100 */ |
||||
real_t Dy[ 100 ]; |
||||
|
||||
/** Column vector of size: 4 */ |
||||
real_t DyN[ 4 ]; |
||||
|
||||
/** Matrix of size: 80 x 4 (row major format) */ |
||||
real_t evGx[ 320 ]; |
||||
|
||||
/** Column vector of size: 80 */ |
||||
real_t evGu[ 80 ]; |
||||
|
||||
/** Row vector of size: 17 */ |
||||
real_t objValueIn[ 17 ]; |
||||
|
||||
/** Row vector of size: 30 */ |
||||
real_t objValueOut[ 30 ]; |
||||
|
||||
/** Matrix of size: 80 x 4 (row major format) */ |
||||
real_t Q1[ 320 ]; |
||||
|
||||
/** Matrix of size: 80 x 5 (row major format) */ |
||||
real_t Q2[ 400 ]; |
||||
|
||||
/** Column vector of size: 20 */ |
||||
real_t R1[ 20 ]; |
||||
|
||||
/** Matrix of size: 20 x 5 (row major format) */ |
||||
real_t R2[ 100 ]; |
||||
|
||||
/** Column vector of size: 80 */ |
||||
real_t S1[ 80 ]; |
||||
|
||||
/** Matrix of size: 4 x 4 (row major format) */ |
||||
real_t QN1[ 16 ]; |
||||
|
||||
/** Matrix of size: 4 x 4 (row major format) */ |
||||
real_t QN2[ 16 ]; |
||||
|
||||
/** Column vector of size: 4 */ |
||||
real_t Dx0[ 4 ]; |
||||
|
||||
/** Matrix of size: 4 x 4 (row major format) */ |
||||
real_t T[ 16 ]; |
||||
|
||||
/** Column vector of size: 840 */ |
||||
real_t E[ 840 ]; |
||||
|
||||
/** Column vector of size: 840 */ |
||||
real_t QE[ 840 ]; |
||||
|
||||
/** Matrix of size: 80 x 4 (row major format) */ |
||||
real_t QGx[ 320 ]; |
||||
|
||||
/** Column vector of size: 80 */ |
||||
real_t Qd[ 80 ]; |
||||
|
||||
/** Column vector of size: 84 */ |
||||
real_t QDy[ 84 ]; |
||||
|
||||
/** Matrix of size: 20 x 4 (row major format) */ |
||||
real_t H10[ 80 ]; |
||||
|
||||
/** Matrix of size: 24 x 24 (row major format) */ |
||||
real_t H[ 576 ]; |
||||
|
||||
/** Column vector of size: 24 */ |
||||
real_t g[ 24 ]; |
||||
|
||||
/** Column vector of size: 24 */ |
||||
real_t lb[ 24 ]; |
||||
|
||||
/** Column vector of size: 24 */ |
||||
real_t ub[ 24 ]; |
||||
|
||||
/** Column vector of size: 24 */ |
||||
real_t x[ 24 ]; |
||||
|
||||
/** Column vector of size: 24 */ |
||||
real_t y[ 24 ]; |
||||
|
||||
|
||||
} ACADOworkspace; |
||||
|
||||
/*
|
||||
* Forward function declarations.
|
||||
*/ |
||||
|
||||
|
||||
/** Performs the integration and sensitivity propagation for one shooting interval.
|
||||
* |
||||
* \param rk_eta Working array to pass the input values and return the results. |
||||
* \param resetIntegrator The internal memory of the integrator can be reset. |
||||
* \param rk_index Number of the shooting interval. |
||||
* |
||||
* \return Status code of the integrator. |
||||
*/ |
||||
int acado_integrate( real_t* const rk_eta, int resetIntegrator, int rk_index ); |
||||
|
||||
/** Export of an ACADO symbolic function.
|
||||
* |
||||
* \param in Input to the exported function. |
||||
* \param out Output of the exported function. |
||||
*/ |
||||
void acado_rhs_forw(const real_t* in, real_t* out); |
||||
|
||||
/** Preparation step of the RTI scheme.
|
||||
* |
||||
* \return Status of the integration module. =0: OK, otherwise the error code. |
||||
*/ |
||||
int acado_preparationStep( ); |
||||
|
||||
/** Feedback/estimation step of the RTI scheme.
|
||||
* |
||||
* \return Status code of the qpOASES QP solver. |
||||
*/ |
||||
int acado_feedbackStep( ); |
||||
|
||||
/** Solver initialization. Must be called once before any other function call.
|
||||
* |
||||
* \return =0: OK, otherwise an error code of a QP solver. |
||||
*/ |
||||
int acado_initializeSolver( ); |
||||
|
||||
/** Initialize shooting nodes by a forward simulation starting from the first node.
|
||||
*/ |
||||
void acado_initializeNodesByForwardSimulation( ); |
||||
|
||||
/** Shift differential variables vector by one interval.
|
||||
* |
||||
* \param strategy Shifting strategy: 1. Initialize node 21 with xEnd. 2. Initialize node 21 by forward simulation. |
||||
* \param xEnd Value for the x vector on the last node. If =0 the old value is used. |
||||
* \param uEnd Value for the u vector on the second to last node. If =0 the old value is used. |
||||
*/ |
||||
void acado_shiftStates( int strategy, real_t* const xEnd, real_t* const uEnd ); |
||||
|
||||
/** Shift controls vector by one interval.
|
||||
* |
||||
* \param uEnd Value for the u vector on the second to last node. If =0 the old value is used. |
||||
*/ |
||||
void acado_shiftControls( real_t* const uEnd ); |
||||
|
||||
/** Get the KKT tolerance of the current iterate.
|
||||
* |
||||
* \return The KKT tolerance value. |
||||
*/ |
||||
real_t acado_getKKT( ); |
||||
|
||||
/** Calculate the objective value.
|
||||
* |
||||
* \return Value of the objective function. |
||||
*/ |
||||
real_t acado_getObjective( ); |
||||
|
||||
|
||||
/*
|
||||
* Extern declarations.
|
||||
*/ |
||||
|
||||
extern ACADOworkspace acadoWorkspace; |
||||
extern ACADOvariables acadoVariables; |
||||
|
||||
/** @} */ |
||||
|
||||
#ifndef __MATLAB__ |
||||
#ifdef __cplusplus |
||||
} /* extern "C" */ |
||||
#endif /* __cplusplus */ |
||||
#endif /* __MATLAB__ */ |
||||
|
||||
#endif /* ACADO_COMMON_H */ |
@ -0,0 +1,231 @@ |
||||
/*
|
||||
* This file was auto-generated using the ACADO Toolkit. |
||||
*
|
||||
* While ACADO Toolkit is free software released under the terms of |
||||
* the GNU Lesser General Public License (LGPL), the generated code |
||||
* as such remains the property of the user who used ACADO Toolkit |
||||
* to generate this code. In particular, user dependent data of the code |
||||
* do not inherit the GNU LGPL license. On the other hand, parts of the |
||||
* generated code that are a direct copy of source code from the |
||||
* ACADO Toolkit or the software tools it is based on, remain, as derived |
||||
* work, automatically covered by the LGPL license. |
||||
*
|
||||
* ACADO Toolkit is distributed in the hope that it will be useful, |
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of |
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
||||
*
|
||||
*/ |
||||
|
||||
|
||||
#include "acado_common.h" |
||||
|
||||
|
||||
void acado_rhs_forw(const real_t* in, real_t* out) |
||||
{ |
||||
const real_t* xd = in; |
||||
const real_t* u = in + 24; |
||||
|
||||
/* Compute outputs: */ |
||||
out[0] = xd[1]; |
||||
out[1] = xd[2]; |
||||
out[2] = u[0]; |
||||
out[3] = (real_t)(1.0000000000000000e+00); |
||||
out[4] = xd[8]; |
||||
out[5] = xd[9]; |
||||
out[6] = xd[10]; |
||||
out[7] = xd[11]; |
||||
out[8] = xd[12]; |
||||
out[9] = xd[13]; |
||||
out[10] = xd[14]; |
||||
out[11] = xd[15]; |
||||
out[12] = (real_t)(0.0000000000000000e+00); |
||||
out[13] = (real_t)(0.0000000000000000e+00); |
||||
out[14] = (real_t)(0.0000000000000000e+00); |
||||
out[15] = (real_t)(0.0000000000000000e+00); |
||||
out[16] = (real_t)(0.0000000000000000e+00); |
||||
out[17] = (real_t)(0.0000000000000000e+00); |
||||
out[18] = (real_t)(0.0000000000000000e+00); |
||||
out[19] = (real_t)(0.0000000000000000e+00); |
||||
out[20] = xd[21]; |
||||
out[21] = xd[22]; |
||||
out[22] = (real_t)(1.0000000000000000e+00); |
||||
out[23] = (real_t)(0.0000000000000000e+00); |
||||
} |
||||
|
||||
/* Fixed step size:0.2 */ |
||||
int acado_integrate( real_t* const rk_eta, int resetIntegrator, int rk_index ) |
||||
{ |
||||
int error; |
||||
|
||||
int run1; |
||||
int numSteps[20] = {1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3}; |
||||
int numInts = numSteps[rk_index]; |
||||
acadoWorkspace.rk_ttt = 0.0000000000000000e+00; |
||||
rk_eta[4] = 1.0000000000000000e+00; |
||||
rk_eta[5] = 0.0000000000000000e+00; |
||||
rk_eta[6] = 0.0000000000000000e+00; |
||||
rk_eta[7] = 0.0000000000000000e+00; |
||||
rk_eta[8] = 0.0000000000000000e+00; |
||||
rk_eta[9] = 1.0000000000000000e+00; |
||||
rk_eta[10] = 0.0000000000000000e+00; |
||||
rk_eta[11] = 0.0000000000000000e+00; |
||||
rk_eta[12] = 0.0000000000000000e+00; |
||||
rk_eta[13] = 0.0000000000000000e+00; |
||||
rk_eta[14] = 1.0000000000000000e+00; |
||||
rk_eta[15] = 0.0000000000000000e+00; |
||||
rk_eta[16] = 0.0000000000000000e+00; |
||||
rk_eta[17] = 0.0000000000000000e+00; |
||||
rk_eta[18] = 0.0000000000000000e+00; |
||||
rk_eta[19] = 1.0000000000000000e+00; |
||||
rk_eta[20] = 0.0000000000000000e+00; |
||||
rk_eta[21] = 0.0000000000000000e+00; |
||||
rk_eta[22] = 0.0000000000000000e+00; |
||||
rk_eta[23] = 0.0000000000000000e+00; |
||||
acadoWorkspace.rk_xxx[24] = rk_eta[24]; |
||||
acadoWorkspace.rk_xxx[25] = rk_eta[25]; |
||||
acadoWorkspace.rk_xxx[26] = rk_eta[26]; |
||||
acadoWorkspace.rk_xxx[27] = rk_eta[27]; |
||||
acadoWorkspace.rk_xxx[28] = rk_eta[28]; |
||||
acadoWorkspace.rk_xxx[29] = rk_eta[29]; |
||||
acadoWorkspace.rk_xxx[30] = rk_eta[30]; |
||||
acadoWorkspace.rk_xxx[31] = rk_eta[31]; |
||||
acadoWorkspace.rk_xxx[32] = rk_eta[32]; |
||||
acadoWorkspace.rk_xxx[33] = rk_eta[33]; |
||||
acadoWorkspace.rk_xxx[34] = rk_eta[34]; |
||||
acadoWorkspace.rk_xxx[35] = rk_eta[35]; |
||||
acadoWorkspace.rk_xxx[36] = rk_eta[36]; |
||||
|
||||
for (run1 = 0; run1 < 1; ++run1) |
||||
{ |
||||
for(run1 = 0; run1 < numInts; run1++ ) { |
||||
acadoWorkspace.rk_xxx[0] = + rk_eta[0]; |
||||
acadoWorkspace.rk_xxx[1] = + rk_eta[1]; |
||||
acadoWorkspace.rk_xxx[2] = + rk_eta[2]; |
||||
acadoWorkspace.rk_xxx[3] = + rk_eta[3]; |
||||
acadoWorkspace.rk_xxx[4] = + rk_eta[4]; |
||||
acadoWorkspace.rk_xxx[5] = + rk_eta[5]; |
||||
acadoWorkspace.rk_xxx[6] = + rk_eta[6]; |
||||
acadoWorkspace.rk_xxx[7] = + rk_eta[7]; |
||||
acadoWorkspace.rk_xxx[8] = + rk_eta[8]; |
||||
acadoWorkspace.rk_xxx[9] = + rk_eta[9]; |
||||
acadoWorkspace.rk_xxx[10] = + rk_eta[10]; |
||||
acadoWorkspace.rk_xxx[11] = + rk_eta[11]; |
||||
acadoWorkspace.rk_xxx[12] = + rk_eta[12]; |
||||
acadoWorkspace.rk_xxx[13] = + rk_eta[13]; |
||||
acadoWorkspace.rk_xxx[14] = + rk_eta[14]; |
||||
acadoWorkspace.rk_xxx[15] = + rk_eta[15]; |
||||
acadoWorkspace.rk_xxx[16] = + rk_eta[16]; |
||||
acadoWorkspace.rk_xxx[17] = + rk_eta[17]; |
||||
acadoWorkspace.rk_xxx[18] = + rk_eta[18]; |
||||
acadoWorkspace.rk_xxx[19] = + rk_eta[19]; |
||||
acadoWorkspace.rk_xxx[20] = + rk_eta[20]; |
||||
acadoWorkspace.rk_xxx[21] = + rk_eta[21]; |
||||
acadoWorkspace.rk_xxx[22] = + rk_eta[22]; |
||||
acadoWorkspace.rk_xxx[23] = + rk_eta[23]; |
||||
acado_rhs_forw( acadoWorkspace.rk_xxx, acadoWorkspace.rk_kkk ); |
||||
acadoWorkspace.rk_xxx[0] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[0] + rk_eta[0]; |
||||
acadoWorkspace.rk_xxx[1] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[1] + rk_eta[1]; |
||||
acadoWorkspace.rk_xxx[2] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[2] + rk_eta[2]; |
||||
acadoWorkspace.rk_xxx[3] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[3] + rk_eta[3]; |
||||
acadoWorkspace.rk_xxx[4] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[4] + rk_eta[4]; |
||||
acadoWorkspace.rk_xxx[5] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[5] + rk_eta[5]; |
||||
acadoWorkspace.rk_xxx[6] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[6] + rk_eta[6]; |
||||
acadoWorkspace.rk_xxx[7] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[7] + rk_eta[7]; |
||||
acadoWorkspace.rk_xxx[8] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[8] + rk_eta[8]; |
||||
acadoWorkspace.rk_xxx[9] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[9] + rk_eta[9]; |
||||
acadoWorkspace.rk_xxx[10] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[10] + rk_eta[10]; |
||||
acadoWorkspace.rk_xxx[11] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[11] + rk_eta[11]; |
||||
acadoWorkspace.rk_xxx[12] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[12] + rk_eta[12]; |
||||
acadoWorkspace.rk_xxx[13] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[13] + rk_eta[13]; |
||||
acadoWorkspace.rk_xxx[14] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[14] + rk_eta[14]; |
||||
acadoWorkspace.rk_xxx[15] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[15] + rk_eta[15]; |
||||
acadoWorkspace.rk_xxx[16] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[16] + rk_eta[16]; |
||||
acadoWorkspace.rk_xxx[17] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[17] + rk_eta[17]; |
||||
acadoWorkspace.rk_xxx[18] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[18] + rk_eta[18]; |
||||
acadoWorkspace.rk_xxx[19] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[19] + rk_eta[19]; |
||||
acadoWorkspace.rk_xxx[20] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[20] + rk_eta[20]; |
||||
acadoWorkspace.rk_xxx[21] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[21] + rk_eta[21]; |
||||
acadoWorkspace.rk_xxx[22] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[22] + rk_eta[22]; |
||||
acadoWorkspace.rk_xxx[23] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[23] + rk_eta[23]; |
||||
acado_rhs_forw( acadoWorkspace.rk_xxx, &(acadoWorkspace.rk_kkk[ 24 ]) ); |
||||
acadoWorkspace.rk_xxx[0] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[24] + rk_eta[0]; |
||||
acadoWorkspace.rk_xxx[1] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[25] + rk_eta[1]; |
||||
acadoWorkspace.rk_xxx[2] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[26] + rk_eta[2]; |
||||
acadoWorkspace.rk_xxx[3] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[27] + rk_eta[3]; |
||||
acadoWorkspace.rk_xxx[4] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[28] + rk_eta[4]; |
||||
acadoWorkspace.rk_xxx[5] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[29] + rk_eta[5]; |
||||
acadoWorkspace.rk_xxx[6] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[30] + rk_eta[6]; |
||||
acadoWorkspace.rk_xxx[7] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[31] + rk_eta[7]; |
||||
acadoWorkspace.rk_xxx[8] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[32] + rk_eta[8]; |
||||
acadoWorkspace.rk_xxx[9] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[33] + rk_eta[9]; |
||||
acadoWorkspace.rk_xxx[10] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[34] + rk_eta[10]; |
||||
acadoWorkspace.rk_xxx[11] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[35] + rk_eta[11]; |
||||
acadoWorkspace.rk_xxx[12] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[36] + rk_eta[12]; |
||||
acadoWorkspace.rk_xxx[13] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[37] + rk_eta[13]; |
||||
acadoWorkspace.rk_xxx[14] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[38] + rk_eta[14]; |
||||
acadoWorkspace.rk_xxx[15] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[39] + rk_eta[15]; |
||||
acadoWorkspace.rk_xxx[16] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[40] + rk_eta[16]; |
||||
acadoWorkspace.rk_xxx[17] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[41] + rk_eta[17]; |
||||
acadoWorkspace.rk_xxx[18] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[42] + rk_eta[18]; |
||||
acadoWorkspace.rk_xxx[19] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[43] + rk_eta[19]; |
||||
acadoWorkspace.rk_xxx[20] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[44] + rk_eta[20]; |
||||
acadoWorkspace.rk_xxx[21] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[45] + rk_eta[21]; |
||||
acadoWorkspace.rk_xxx[22] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[46] + rk_eta[22]; |
||||
acadoWorkspace.rk_xxx[23] = + (real_t)9.9999999999999964e-02*acadoWorkspace.rk_kkk[47] + rk_eta[23]; |
||||
acado_rhs_forw( acadoWorkspace.rk_xxx, &(acadoWorkspace.rk_kkk[ 48 ]) ); |
||||
acadoWorkspace.rk_xxx[0] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[48] + rk_eta[0]; |
||||
acadoWorkspace.rk_xxx[1] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[49] + rk_eta[1]; |
||||
acadoWorkspace.rk_xxx[2] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[50] + rk_eta[2]; |
||||
acadoWorkspace.rk_xxx[3] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[51] + rk_eta[3]; |
||||
acadoWorkspace.rk_xxx[4] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[52] + rk_eta[4]; |
||||
acadoWorkspace.rk_xxx[5] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[53] + rk_eta[5]; |
||||
acadoWorkspace.rk_xxx[6] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[54] + rk_eta[6]; |
||||
acadoWorkspace.rk_xxx[7] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[55] + rk_eta[7]; |
||||
acadoWorkspace.rk_xxx[8] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[56] + rk_eta[8]; |
||||
acadoWorkspace.rk_xxx[9] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[57] + rk_eta[9]; |
||||
acadoWorkspace.rk_xxx[10] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[58] + rk_eta[10]; |
||||
acadoWorkspace.rk_xxx[11] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[59] + rk_eta[11]; |
||||
acadoWorkspace.rk_xxx[12] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[60] + rk_eta[12]; |
||||
acadoWorkspace.rk_xxx[13] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[61] + rk_eta[13]; |
||||
acadoWorkspace.rk_xxx[14] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[62] + rk_eta[14]; |
||||
acadoWorkspace.rk_xxx[15] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[63] + rk_eta[15]; |
||||
acadoWorkspace.rk_xxx[16] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[64] + rk_eta[16]; |
||||
acadoWorkspace.rk_xxx[17] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[65] + rk_eta[17]; |
||||
acadoWorkspace.rk_xxx[18] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[66] + rk_eta[18]; |
||||
acadoWorkspace.rk_xxx[19] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[67] + rk_eta[19]; |
||||
acadoWorkspace.rk_xxx[20] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[68] + rk_eta[20]; |
||||
acadoWorkspace.rk_xxx[21] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[69] + rk_eta[21]; |
||||
acadoWorkspace.rk_xxx[22] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[70] + rk_eta[22]; |
||||
acadoWorkspace.rk_xxx[23] = + (real_t)1.9999999999999993e-01*acadoWorkspace.rk_kkk[71] + rk_eta[23]; |
||||
acado_rhs_forw( acadoWorkspace.rk_xxx, &(acadoWorkspace.rk_kkk[ 72 ]) ); |
||||
rk_eta[0] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[0] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[24] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[48] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[72]; |
||||
rk_eta[1] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[1] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[25] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[49] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[73]; |
||||
rk_eta[2] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[2] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[26] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[50] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[74]; |
||||
rk_eta[3] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[3] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[27] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[51] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[75]; |
||||
rk_eta[4] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[4] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[28] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[52] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[76]; |
||||
rk_eta[5] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[5] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[29] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[53] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[77]; |
||||
rk_eta[6] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[6] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[30] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[54] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[78]; |
||||
rk_eta[7] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[7] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[31] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[55] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[79]; |
||||
rk_eta[8] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[8] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[32] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[56] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[80]; |
||||
rk_eta[9] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[9] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[33] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[57] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[81]; |
||||
rk_eta[10] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[10] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[34] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[58] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[82]; |
||||
rk_eta[11] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[11] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[35] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[59] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[83]; |
||||
rk_eta[12] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[12] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[36] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[60] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[84]; |
||||
rk_eta[13] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[13] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[37] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[61] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[85]; |
||||
rk_eta[14] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[14] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[38] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[62] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[86]; |
||||
rk_eta[15] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[15] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[39] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[63] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[87]; |
||||
rk_eta[16] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[16] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[40] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[64] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[88]; |
||||
rk_eta[17] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[17] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[41] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[65] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[89]; |
||||
rk_eta[18] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[18] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[42] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[66] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[90]; |
||||
rk_eta[19] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[19] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[43] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[67] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[91]; |
||||
rk_eta[20] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[20] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[44] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[68] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[92]; |
||||
rk_eta[21] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[21] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[45] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[69] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[93]; |
||||
rk_eta[22] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[22] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[46] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[70] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[94]; |
||||
rk_eta[23] += + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[23] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[47] + (real_t)6.6666666666666638e-02*acadoWorkspace.rk_kkk[71] + (real_t)3.3333333333333319e-02*acadoWorkspace.rk_kkk[95]; |
||||
acadoWorkspace.rk_ttt += 1.0000000000000000e+00; |
||||
} |
||||
} |
||||
error = 0; |
||||
return error; |
||||
} |
||||
|
@ -0,0 +1,70 @@ |
||||
/*
|
||||
* This file was auto-generated using the ACADO Toolkit. |
||||
*
|
||||
* While ACADO Toolkit is free software released under the terms of |
||||
* the GNU Lesser General Public License (LGPL), the generated code |
||||
* as such remains the property of the user who used ACADO Toolkit |
||||
* to generate this code. In particular, user dependent data of the code |
||||
* do not inherit the GNU LGPL license. On the other hand, parts of the |
||||
* generated code that are a direct copy of source code from the |
||||
* ACADO Toolkit or the software tools it is based on, remain, as derived |
||||
* work, automatically covered by the LGPL license. |
||||
*
|
||||
* ACADO Toolkit is distributed in the hope that it will be useful, |
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of |
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
||||
*
|
||||
*/ |
||||
|
||||
|
||||
extern "C" |
||||
{ |
||||
#include "acado_common.h" |
||||
} |
||||
|
||||
#include "INCLUDE/QProblemB.hpp" |
||||
|
||||
#if ACADO_COMPUTE_COVARIANCE_MATRIX == 1 |
||||
#include "INCLUDE/EXTRAS/SolutionAnalysis.hpp" |
||||
#endif /* ACADO_COMPUTE_COVARIANCE_MATRIX */ |
||||
|
||||
static int acado_nWSR; |
||||
|
||||
|
||||
|
||||
#if ACADO_COMPUTE_COVARIANCE_MATRIX == 1 |
||||
static SolutionAnalysis acado_sa; |
||||
#endif /* ACADO_COMPUTE_COVARIANCE_MATRIX */ |
||||
|
||||
int acado_solve( void ) |
||||
{ |
||||
acado_nWSR = QPOASES_NWSRMAX; |
||||
|
||||
QProblemB qp( 24 ); |
||||
|
||||
returnValue retVal = qp.init(acadoWorkspace.H, acadoWorkspace.g, acadoWorkspace.lb, acadoWorkspace.ub, acado_nWSR, acadoWorkspace.y); |
||||
|
||||
qp.getPrimalSolution( acadoWorkspace.x ); |
||||
qp.getDualSolution( acadoWorkspace.y ); |
||||
|
||||
#if ACADO_COMPUTE_COVARIANCE_MATRIX == 1 |
||||
|
||||
if (retVal != SUCCESSFUL_RETURN) |
||||
return (int)retVal; |
||||
|
||||
retVal = acado_sa.getHessianInverse( &qp,var ); |
||||
|
||||
#endif /* ACADO_COMPUTE_COVARIANCE_MATRIX */ |
||||
|
||||
return (int)retVal; |
||||
} |
||||
|
||||
int acado_getNWSR( void ) |
||||
{ |
||||
return acado_nWSR; |
||||
} |
||||
|
||||
const char* acado_getErrorString( int error ) |
||||
{ |
||||
return MessageHandling::getErrorString( error ); |
||||
} |
@ -0,0 +1,65 @@ |
||||
/*
|
||||
* This file was auto-generated using the ACADO Toolkit. |
||||
*
|
||||
* While ACADO Toolkit is free software released under the terms of |
||||
* the GNU Lesser General Public License (LGPL), the generated code |
||||
* as such remains the property of the user who used ACADO Toolkit |
||||
* to generate this code. In particular, user dependent data of the code |
||||
* do not inherit the GNU LGPL license. On the other hand, parts of the |
||||
* generated code that are a direct copy of source code from the |
||||
* ACADO Toolkit or the software tools it is based on, remain, as derived |
||||
* work, automatically covered by the LGPL license. |
||||
*
|
||||
* ACADO Toolkit is distributed in the hope that it will be useful, |
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of |
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
||||
*
|
||||
*/ |
||||
|
||||
|
||||
#ifndef QPOASES_HEADER |
||||
#define QPOASES_HEADER |
||||
|
||||
#ifdef PC_DEBUG |
||||
#include <stdio.h> |
||||
#endif /* PC_DEBUG */ |
||||
|
||||
#include <math.h> |
||||
|
||||
#ifdef __cplusplus |
||||
#define EXTERNC extern "C" |
||||
#else |
||||
#define EXTERNC |
||||
#endif |
||||
|
||||
/*
|
||||
* A set of options for qpOASES |
||||
*/ |
||||
|
||||
/** Maximum number of optimization variables. */ |
||||
#define QPOASES_NVMAX 24 |
||||
/** Maximum number of constraints. */ |
||||
#define QPOASES_NCMAX 0 |
||||
/** Maximum number of working set recalculations. */ |
||||
#define QPOASES_NWSRMAX 500 |
||||
/** Print level for qpOASES. */ |
||||
#define QPOASES_PRINTLEVEL PL_NONE |
||||
/** The value of EPS */ |
||||
#define QPOASES_EPS 2.221e-16 |
||||
/** Internally used floating point type */ |
||||
typedef double real_t; |
||||
|
||||
/*
|
||||
* Forward function declarations |
||||
*/ |
||||
|
||||
/** A function that calls the QP solver */ |
||||
EXTERNC int acado_solve( void ); |
||||
|
||||
/** Get the number of active set changes */ |
||||
EXTERNC int acado_getNWSR( void ); |
||||
|
||||
/** Get the error string. */ |
||||
const char* acado_getErrorString( int error ); |
||||
|
||||
#endif /* QPOASES_HEADER */ |
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,32 @@ |
||||
import os |
||||
|
||||
from cffi import FFI |
||||
from common.ffi_wrapper import suffix |
||||
|
||||
mpc_dir = os.path.join(os.path.dirname(os.path.abspath(__file__))) |
||||
libmpc_fn = os.path.join(mpc_dir, "libmpc"+suffix()) |
||||
|
||||
ffi = FFI() |
||||
ffi.cdef(""" |
||||
|
||||
typedef struct { |
||||
double x_ego, v_ego, a_ego; |
||||
} state_t; |
||||
|
||||
|
||||
typedef struct { |
||||
double x_ego[21]; |
||||
double v_ego[21]; |
||||
double a_ego[21]; |
||||
double t[21]; |
||||
double j_ego[20]; |
||||
double cost; |
||||
} log_t; |
||||
|
||||
|
||||
void init(double xCost, double vCost, double aCost, double accelCost, double jerkCost); |
||||
void init_with_simulation(double v_ego); |
||||
int run_mpc(state_t * x0, log_t * solution, double x_poly[4], double v_poly[4], double a_poly[4]); |
||||
""") |
||||
|
||||
libmpc = ffi.dlopen(libmpc_fn) |
@ -0,0 +1,141 @@ |
||||
#include "acado_common.h" |
||||
#include "acado_auxiliary_functions.h" |
||||
|
||||
#include <stdio.h> |
||||
#include <math.h> |
||||
|
||||
#define NX ACADO_NX /* Number of differential state variables. */ |
||||
#define NXA ACADO_NXA /* Number of algebraic variables. */ |
||||
#define NU ACADO_NU /* Number of control inputs. */ |
||||
#define NOD ACADO_NOD /* Number of online data values. */ |
||||
|
||||
#define NY ACADO_NY /* Number of measurements/references on nodes 0..N - 1. */ |
||||
#define NYN ACADO_NYN /* Number of measurements/references on node N. */ |
||||
|
||||
#define N ACADO_N /* Number of intervals in the horizon. */ |
||||
|
||||
ACADOvariables acadoVariables; |
||||
ACADOworkspace acadoWorkspace; |
||||
|
||||
typedef struct { |
||||
double x_ego, v_ego, a_ego; |
||||
} state_t; |
||||
|
||||
|
||||
typedef struct { |
||||
double x_ego[N+1]; |
||||
double v_ego[N+1]; |
||||
double a_ego[N+1]; |
||||
double t[N+1]; |
||||
double j_ego[N]; |
||||
double cost; |
||||
} log_t; |
||||
|
||||
void init(double xCost, double vCost, double aCost, double accelCost, double jerkCost){ |
||||
acado_initializeSolver(); |
||||
int i; |
||||
const int STEP_MULTIPLIER = 3; |
||||
|
||||
/* Initialize the states and controls. */ |
||||
for (i = 0; i < NX * (N + 1); ++i) acadoVariables.x[ i ] = 0.0; |
||||
for (i = 0; i < NU * N; ++i) acadoVariables.u[ i ] = 0.0; |
||||
|
||||
/* Initialize the measurements/reference. */ |
||||
for (i = 0; i < NY * N; ++i) acadoVariables.y[ i ] = 0.0; |
||||
for (i = 0; i < NYN; ++i) acadoVariables.yN[ i ] = 0.0; |
||||
|
||||
/* MPC: initialize the current state feedback. */ |
||||
for (i = 0; i < NX; ++i) acadoVariables.x0[ i ] = 0.0; |
||||
// Set weights
|
||||
|
||||
for (i = 0; i < N; i++) { |
||||
int f = 1; |
||||
if (i > 4){ |
||||
f = STEP_MULTIPLIER; |
||||
} |
||||
// Setup diagonal entries
|
||||
acadoVariables.W[NY*NY*i + (NY+1)*0] = xCost * f; |
||||
acadoVariables.W[NY*NY*i + (NY+1)*1] = vCost * f; |
||||
acadoVariables.W[NY*NY*i + (NY+1)*2] = aCost * f; |
||||
acadoVariables.W[NY*NY*i + (NY+1)*3] = accelCost * f; |
||||
acadoVariables.W[NY*NY*i + (NY+1)*4] = jerkCost * f; |
||||
} |
||||
acadoVariables.WN[(NYN+1)*0] = xCost * STEP_MULTIPLIER; |
||||
acadoVariables.WN[(NYN+1)*1] = vCost * STEP_MULTIPLIER; |
||||
acadoVariables.WN[(NYN+1)*2] = aCost * STEP_MULTIPLIER; |
||||
acadoVariables.WN[(NYN+1)*3] = accelCost * STEP_MULTIPLIER; |
||||
|
||||
} |
||||
|
||||
void init_with_simulation(double v_ego){ |
||||
int i; |
||||
|
||||
double x_ego = 0.0; |
||||
|
||||
double dt = 0.2; |
||||
double t = 0.0; |
||||
|
||||
for (i = 0; i < N + 1; ++i){ |
||||
if (i > 4){ |
||||
dt = 0.6; |
||||
} |
||||
|
||||
acadoVariables.x[i*NX] = x_ego; |
||||
acadoVariables.x[i*NX+1] = v_ego; |
||||
acadoVariables.x[i*NX+2] = 0; |
||||
acadoVariables.x[i*NX+3] = t; |
||||
|
||||
x_ego += v_ego * dt; |
||||
t += dt; |
||||
} |
||||
|
||||
for (i = 0; i < NU * N; ++i) acadoVariables.u[ i ] = 0.0; |
||||
for (i = 0; i < NY * N; ++i) acadoVariables.y[ i ] = 0.0; |
||||
for (i = 0; i < NYN; ++i) acadoVariables.yN[ i ] = 0.0; |
||||
} |
||||
|
||||
int run_mpc(state_t * x0, log_t * solution, |
||||
double x_poly[4], double v_poly[4], double a_poly[4]){ |
||||
int i; |
||||
|
||||
for (i = 0; i < N + 1; ++i){ |
||||
acadoVariables.od[i*NOD+0] = x_poly[0]; |
||||
acadoVariables.od[i*NOD+1] = x_poly[1]; |
||||
acadoVariables.od[i*NOD+2] = x_poly[2]; |
||||
acadoVariables.od[i*NOD+3] = x_poly[3]; |
||||
|
||||
acadoVariables.od[i*NOD+4] = v_poly[0]; |
||||
acadoVariables.od[i*NOD+5] = v_poly[1]; |
||||
acadoVariables.od[i*NOD+6] = v_poly[2]; |
||||
acadoVariables.od[i*NOD+7] = v_poly[3]; |
||||
|
||||
acadoVariables.od[i*NOD+8] = a_poly[0]; |
||||
acadoVariables.od[i*NOD+9] = a_poly[1]; |
||||
acadoVariables.od[i*NOD+10] = a_poly[2]; |
||||
acadoVariables.od[i*NOD+11] = a_poly[3]; |
||||
} |
||||
|
||||
acadoVariables.x[0] = acadoVariables.x0[0] = x0->x_ego; |
||||
acadoVariables.x[1] = acadoVariables.x0[1] = x0->v_ego; |
||||
acadoVariables.x[2] = acadoVariables.x0[2] = x0->a_ego; |
||||
acadoVariables.x[3] = acadoVariables.x0[3] = 0; |
||||
|
||||
acado_preparationStep(); |
||||
acado_feedbackStep(); |
||||
|
||||
for (i = 0; i <= N; i++){ |
||||
solution->x_ego[i] = acadoVariables.x[i*NX]; |
||||
solution->v_ego[i] = acadoVariables.x[i*NX+1]; |
||||
solution->a_ego[i] = acadoVariables.x[i*NX+2]; |
||||
solution->t[i] = acadoVariables.x[i*NX+3]; |
||||
|
||||
if (i < N){ |
||||
solution->j_ego[i] = acadoVariables.u[i]; |
||||
} |
||||
} |
||||
solution->cost = acado_getObjective(); |
||||
|
||||
// Dont shift states here. Current solution is closer to next timestep than if
|
||||
// we shift by 0.1 seconds.
|
||||
return acado_getNWSR(); |
||||
} |
@ -0,0 +1,75 @@ |
||||
#!/usr/bin/env python3 |
||||
import numpy as np |
||||
|
||||
import matplotlib.pyplot as plt |
||||
|
||||
from selfdrive.controls.lib.longitudinal_mpc_model import libmpc_py |
||||
|
||||
libmpc = libmpc_py.libmpc |
||||
|
||||
dt = 1 |
||||
speeds = [6.109375, 5.9765625, 6.6367188, 7.6875, 8.7578125, 9.4375, 10.21875, 11.070312, 11.679688, 12.21875] |
||||
accelerations = [0.15405273, 0.39575195, 0.36669922, 0.29248047, 0.27856445, 0.27832031, 0.29736328, 0.22705078, 0.16003418, 0.15185547] |
||||
ts = [t * dt for t in range(len(speeds))] |
||||
|
||||
# TODO: Get from actual model packet |
||||
x = 0.0 |
||||
positions = [] |
||||
for v in speeds: |
||||
positions.append(x) |
||||
x += v * dt |
||||
|
||||
|
||||
# Polyfit trajectories |
||||
x_poly = list(map(float, np.polyfit(ts, positions, 3))) |
||||
v_poly = list(map(float, np.polyfit(ts, speeds, 3))) |
||||
a_poly = list(map(float, np.polyfit(ts, accelerations, 3))) |
||||
|
||||
x_poly = libmpc_py.ffi.new("double[4]", x_poly) |
||||
v_poly = libmpc_py.ffi.new("double[4]", v_poly) |
||||
a_poly = libmpc_py.ffi.new("double[4]", a_poly) |
||||
|
||||
cur_state = libmpc_py.ffi.new("state_t *") |
||||
cur_state[0].x_ego = 0 |
||||
cur_state[0].v_ego = 10 |
||||
cur_state[0].a_ego = 0 |
||||
|
||||
libmpc.init(1.0, 1.0, 1.0, 1.0, 1.0) |
||||
|
||||
mpc_solution = libmpc_py.ffi.new("log_t *") |
||||
libmpc.init_with_simulation(cur_state[0].v_ego) |
||||
|
||||
libmpc.run_mpc(cur_state, mpc_solution, x_poly, v_poly, a_poly) |
||||
|
||||
# Converge to solution |
||||
for _ in range(10): |
||||
libmpc.run_mpc(cur_state, mpc_solution, x_poly, v_poly, a_poly) |
||||
|
||||
|
||||
ts_sol = list(mpc_solution[0].t) |
||||
x_sol = list(mpc_solution[0].x_ego) |
||||
v_sol = list(mpc_solution[0].v_ego) |
||||
a_sol = list(mpc_solution[0].a_ego) |
||||
|
||||
|
||||
plt.figure() |
||||
plt.subplot(3, 1, 1) |
||||
plt.plot(ts, positions, 'k--') |
||||
plt.plot(ts_sol, x_sol) |
||||
plt.ylabel('Position [m]') |
||||
plt.xlabel('Time [s]') |
||||
|
||||
plt.subplot(3, 1, 2) |
||||
plt.plot(ts, speeds, 'k--') |
||||
plt.plot(ts_sol, v_sol) |
||||
plt.xlabel('Time [s]') |
||||
plt.ylabel('Speed [m/s]') |
||||
|
||||
plt.subplot(3, 1, 3) |
||||
plt.plot(ts, accelerations, 'k--') |
||||
plt.plot(ts_sol, a_sol) |
||||
|
||||
plt.xlabel('Time [s]') |
||||
plt.ylabel('Acceleration [m/s^2]') |
||||
|
||||
plt.show() |
Loading…
Reference in new issue