You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
111 lines
3.5 KiB
111 lines
3.5 KiB
#include "acado_common.h"
|
|
#include "acado_auxiliary_functions.h"
|
|
#include "common/modeldata.h"
|
|
#include <stdio.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, y, psi, tire_angle, tire_angle_rate;
|
|
} state_t;
|
|
|
|
typedef struct {
|
|
double x[N+1];
|
|
double y[N+1];
|
|
double psi[N+1];
|
|
double tire_angle[N+1];
|
|
double tire_angle_rate[N];
|
|
double cost;
|
|
} log_t;
|
|
|
|
void init_weights(double pathCost, double headingCost, double steerRateCost){
|
|
int i;
|
|
const int STEP_MULTIPLIER = 3.0;
|
|
|
|
for (i = 0; i < N; i++) {
|
|
double f = 20 * (T_IDXS[i+1] - T_IDXS[i]);
|
|
// Setup diagonal entries
|
|
acadoVariables.W[NY*NY*i + (NY+1)*0] = pathCost * f;
|
|
acadoVariables.W[NY*NY*i + (NY+1)*1] = headingCost * f;
|
|
acadoVariables.W[NY*NY*i + (NY+1)*2] = steerRateCost * f;
|
|
}
|
|
acadoVariables.WN[(NYN+1)*0] = pathCost * STEP_MULTIPLIER;
|
|
acadoVariables.WN[(NYN+1)*1] = headingCost * STEP_MULTIPLIER;
|
|
}
|
|
|
|
void init(double pathCost, double headingCost, double steerRateCost){
|
|
acado_initializeSolver();
|
|
int i;
|
|
|
|
/* 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;
|
|
|
|
init_weights(pathCost, headingCost, steerRateCost);
|
|
}
|
|
|
|
int run_mpc(state_t * x0, log_t * solution, double v_ego,
|
|
double rotation_radius, double target_y[N+1], double target_psi[N+1]){
|
|
|
|
int i;
|
|
|
|
for (i = 0; i <= NOD * N; i+= NOD){
|
|
acadoVariables.od[i] = v_ego;
|
|
acadoVariables.od[i+1] = rotation_radius;
|
|
}
|
|
for (i = 0; i < N; i+= 1){
|
|
acadoVariables.y[NY*i + 0] = target_y[i];
|
|
acadoVariables.y[NY*i + 1] = (v_ego + 5.0) * target_psi[i];
|
|
acadoVariables.y[NY*i + 2] = 0.0;
|
|
}
|
|
acadoVariables.yN[0] = target_y[N];
|
|
acadoVariables.yN[1] = (2.0 * v_ego + 5.0) * target_psi[N];
|
|
|
|
acadoVariables.x0[0] = x0->x;
|
|
acadoVariables.x0[1] = x0->y;
|
|
acadoVariables.x0[2] = x0->psi;
|
|
acadoVariables.x0[3] = x0->tire_angle;
|
|
|
|
|
|
acado_preparationStep();
|
|
acado_feedbackStep();
|
|
|
|
/* printf("lat its: %d\n", acado_getNWSR()); // n iterations
|
|
printf("Objective: %.6f\n", acado_getObjective()); // solution cost */
|
|
|
|
for (i = 0; i <= N; i++){
|
|
solution->x[i] = acadoVariables.x[i*NX];
|
|
solution->y[i] = acadoVariables.x[i*NX+1];
|
|
solution->psi[i] = acadoVariables.x[i*NX+2];
|
|
solution->tire_angle[i] = acadoVariables.x[i*NX+3];
|
|
if (i < N){
|
|
solution->tire_angle_rate[i] = acadoVariables.u[i];
|
|
}
|
|
}
|
|
solution->cost = acado_getObjective();
|
|
|
|
// Dont shift states here. Current solution is closer to next timestep than if
|
|
// we use the old solution as a starting point
|
|
//acado_shiftStates(2, 0, 0);
|
|
//acado_shiftControls( 0 );
|
|
|
|
return acado_getNWSR();
|
|
}
|
|
|