Files
sunnypilot/selfdrive/controls/lib/lead_mpc_lib/generator.cpp
HaraldSchafer be5ddd25cd Refactor long (#21433)
* refactor

* needs casting

* tests pass

* fix that test

* refactor in controls

* lets not go crazy

* change of names

* use constants

* better naming

* renamed

* soft constraints

* compile slack variables

* rm git conflict

* add slack variables

* unused

* new edition

* fcw

* fix tests

* dividing causes problems

* was way too slow

* take a step back

* byeeee

* for another time

* bad idxs

* little more cpu for cruise mpc

* update refs

* these limits seem fine

* rename

* test model timings fails sometimes

* add default

* save some cpu

* Revert "little more cpu for cruise mpc"

This reverts commit f0a8163ec90e8dc1eabb3c4a4268ad330d23374d.

* Revert "test model timings fails sometimes"

This reverts commit d259d845710ed2cbeb28b383e2600476527d4838.

* update refs

* less cpu

* Revert "Revert "test model timings fails sometimes""

This reverts commit e0263050d9929bfc7ee70c9788234541a4a8461c.

* Revert "less cpu"

This reverts commit 679007472bc2013e7fafb7b17de7a43d6f82359a.

* cleanup

* not too much until we clean up mpc

* more cost on jerk

* change ref

* add todo

* new ref

* indentation
2021-07-07 19:42:26 -07:00

98 lines
2.3 KiB
C++

#include <acado_code_generation.hpp>
const int controlHorizon = 50;
using namespace std;
#define G 9.81
#define TR 1.8
#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))
#define NORM_RW_ERROR(v_ego, v_l, p) ((RW(v_ego, v_l) + 4.0 - p)/(sqrt(v_ego + 0.5) + 0.1))
int main( )
{
USING_NAMESPACE_ACADO
DifferentialEquation f;
DifferentialState x_ego, v_ego, a_ego;
OnlineData x_l, v_l;
Control j_ego;
auto desired = 4.0 + RW(v_ego, v_l);
auto d_l = x_l - x_ego;
// Equations of motion
f << dot(x_ego) == v_ego;
f << dot(v_ego) == a_ego;
f << dot(a_ego) == j_ego;
// Running cost
Function h;
h << exp(0.3 * NORM_RW_ERROR(v_ego, v_l, d_l)) - 1;
h << (d_l - desired) / (0.05 * v_ego + 0.5);
h << a_ego * (0.1 * v_ego + 1.0);
h << j_ego * (0.1 * v_ego + 1.0);
// Weights are defined in mpc.
BMatrix Q(4,4); Q.setAll(true);
// Terminal cost
Function hN;
hN << exp(0.3 * NORM_RW_ERROR(v_ego, v_l, d_l)) - 1;
hN << (d_l - desired) / (0.05 * v_ego + 0.5);
hN << a_ego * (0.1 * v_ego + 1.0);
// Weights are defined in mpc.
BMatrix QN(3,3); QN.setAll(true);
// Non uniform time grid
// First 5 timesteps are 0.2, after that it's 0.6
DMatrix numSteps(20, 1);
for (int i = 0; i < 5; i++){
numSteps(i) = 1;
}
for (int i = 5; i < 20; i++){
numSteps(i) = 3;
}
// Setup Optimal Control Problem
const double tStart = 0.0;
const double tEnd = 10.0;
OCP ocp( tStart, tEnd, numSteps);
ocp.subjectTo(f);
ocp.minimizeLSQ(Q, h);
ocp.minimizeLSQEndTerm(QN, hN);
ocp.subjectTo( 0.0 <= v_ego);
ocp.setNOD(2);
OCPexport mpc(ocp);
mpc.set( HESSIAN_APPROXIMATION, GAUSS_NEWTON );
mpc.set( DISCRETIZATION_TYPE, MULTIPLE_SHOOTING );
mpc.set( INTEGRATOR_TYPE, INT_RK4 );
mpc.set( NUM_INTEGRATOR_STEPS, controlHorizon);
mpc.set( MAX_NUM_QP_ITERATIONS, 50);
mpc.set( CG_USE_VARIABLE_WEIGHTING_MATRIX, YES);
mpc.set( SPARSE_QP_SOLUTION, CONDENSING );
mpc.set( QP_SOLVER, QP_QPOASES );
mpc.set( HOTSTART_QP, YES );
mpc.set( GENERATE_TEST_FILE, NO);
mpc.set( GENERATE_MAKE_FILE, NO );
mpc.set( GENERATE_MATLAB_INTERFACE, NO );
mpc.set( GENERATE_SIMULINK_INTERFACE, NO );
if (mpc.exportCode( "lib_mpc_export" ) != SUCCESSFUL_RETURN)
exit( EXIT_FAILURE );
mpc.printDimensionsQP( );
return EXIT_SUCCESS;
}