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104 lines
2.5 KiB
104 lines
2.5 KiB
#include <acado_code_generation.hpp>
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const int controlHorizon = 50;
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const double samplingTime = 0.2;
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using namespace std;
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#define G 9.81
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#define TR 1.8
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#define RW(v_ego, v_l) (v_ego * TR - (v_l - v_ego) * TR + v_ego*v_ego/(2*G) - v_l*v_l / (2*G))
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#define NORM_RW_ERROR(v_ego, v_l, p) ((RW(v_ego, v_l) + 4.0 - p)/(sqrt(v_ego + 0.5) + 0.1))
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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;
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DifferentialState x_l, v_l, a_l;
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OnlineData lambda;
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Control j_ego;
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auto desired = 4.0 + RW(v_ego, v_l);
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auto d_l = x_l - x_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(x_l) == v_l;
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f << dot(v_l) == a_l;
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f << dot(a_l) == -lambda * a_l;
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// Running cost
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Function h;
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h << exp(0.3 * NORM_RW_ERROR(v_ego, v_l, d_l)) - exp(0.3 * NORM_RW_ERROR(v_ego, v_l, desired));
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h << (d_l - desired) / (0.1 * v_ego + 0.5);
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h << a_ego * (1.0 + v_ego / 10.0);
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h << j_ego * (1.0 + v_ego / 10.0);
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// Weights are defined in mpc.
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BMatrix Q(4,4); Q.setAll(true);
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// Terminal cost
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Function hN;
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hN << exp(0.3 * NORM_RW_ERROR(v_ego, v_l, d_l)) - exp(0.3 * NORM_RW_ERROR(v_ego, v_l, desired));
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hN << (d_l - desired) / (0.1 * v_ego + 0.5);
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hN << a_ego * (1.0 + v_ego / 10.0);
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// Weights are defined in mpc.
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BMatrix QN(3,3); 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(1);
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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( "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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}
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