void OptimalControlProblem::set_reference_point(const ReferenceVector &in,
uint32_t i) {
state_reference[i] = in.segment<NMPC_STATE_DIM>(0);
if(i > 0 && i <= OCP_HORIZON_LENGTH) {
control_reference[i-1] =
in.segment<NMPC_CONTROL_DIM>(NMPC_STATE_DIM);
solve_ivps(i-1);
real_t g[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> g_map(g);
real_t C[(NMPC_STATE_DIM-1)*NMPC_GRADIENT_DIM];
Eigen::Map<ContinuityConstraintMatrix> C_map(C);
real_t c[NMPC_DELTA_DIM];
Eigen::Map<DeltaVector> c_map(c);
real_t zLow[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> zLow_map(zLow);
real_t zUpp[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> zUpp_map(zUpp);
zLow_map.segment<NMPC_DELTA_DIM>(0) = lower_state_bound;
zUpp_map.segment<NMPC_DELTA_DIM>(0) = upper_state_bound;
return_t status_flag;
/* Gradient vector fixed to zero. */
g_map = GradientVector::Zero();
/* Continuity constraint constant term fixed to zero. */
c_map = integration_residuals[i-1];
/* Copy the relevant data into the qpDUNES arrays. */
C_map = jacobians[i-1];
zLow_map.segment<NMPC_CONTROL_DIM>(NMPC_DELTA_DIM) =
lower_control_bound - control_reference[i-1];
zUpp_map.segment<NMPC_CONTROL_DIM>(NMPC_DELTA_DIM) =
upper_control_bound - control_reference[i-1];
status_flag = qpDUNES_updateIntervalData(
&qp_data, qp_data.intervals[i-1],
0, g, C, c, zLow, zUpp, 0, 0, 0, 0);
AssertOK(status_flag);
qpDUNES_indicateDataChange(&qp_data);
}
}
double ProblemDescription::evaluateCollisionFunction( const double * xi,
double * g)
{
//TODO throw error.
assert( collision_function );
prepareData( xi );
double value;
if ( g ){
MatMap g_map( g, N(), M() );
value = collision_function->evaluate( trajectory, g_map );
if ( doing_covariant ){ metric.multiplyLowerInverse( g_map ); }
}else {
value = collision_function->evaluate( trajectory );
}
return value;
}
/*
Uses all of the information calculated so far to set up the various qpDUNES
datastructures in preparation for the feedback step.
This is really inefficient right now – there's heaps of probably unnecessary
copying going on.
*/
void OptimalControlProblem::initialise_qp() {
uint32_t i;
real_t Q[NMPC_DELTA_DIM*NMPC_DELTA_DIM];
Eigen::Map<StateWeightMatrix> Q_map(Q);
real_t R[NMPC_CONTROL_DIM*NMPC_CONTROL_DIM];
Eigen::Map<ControlWeightMatrix> R_map(R);
real_t P[NMPC_DELTA_DIM*NMPC_DELTA_DIM];
Eigen::Map<StateWeightMatrix> P_map(P);
real_t g[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> g_map(g);
real_t C[(NMPC_STATE_DIM-1)*NMPC_GRADIENT_DIM];
Eigen::Map<ContinuityConstraintMatrix> C_map(C);
real_t c[NMPC_DELTA_DIM];
Eigen::Map<DeltaVector> c_map(c);
real_t zLow[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> zLow_map(zLow);
real_t zUpp[NMPC_GRADIENT_DIM];
Eigen::Map<GradientVector> zUpp_map(zUpp);
zLow_map.segment<NMPC_DELTA_DIM>(0) = lower_state_bound;
zUpp_map.segment<NMPC_DELTA_DIM>(0) = upper_state_bound;
/* Set up problem dimensions. */
/* TODO: Determine number of affine constraints (D), and add them. */
qpDUNES_setup(
&qp_data,
OCP_HORIZON_LENGTH,
NMPC_DELTA_DIM,
NMPC_CONTROL_DIM,
0,
&qp_options);
return_t status_flag;
/* Gradient vector fixed to zero. */
g_map = GradientVector::Zero();
/* Continuity constraint constant term fixed to zero. */
c_map = DeltaVector::Zero();
/* Zero Jacobians for now */
C_map = ContinuityConstraintMatrix::Zero();
Q_map = state_weights;
R_map = control_weights;
/* Copy the relevant data into the qpDUNES arrays. */
zLow_map.segment<NMPC_CONTROL_DIM>(NMPC_DELTA_DIM) = lower_control_bound;
zUpp_map.segment<NMPC_CONTROL_DIM>(NMPC_DELTA_DIM) = upper_control_bound;
for(i = 0; i < OCP_HORIZON_LENGTH; i++) {
status_flag = qpDUNES_setupRegularInterval(
&qp_data, qp_data.intervals[i],
0, Q, R, 0, g, C, 0, 0, c, zLow, zUpp, 0, 0, 0, 0, 0, 0, 0);
AssertOK(status_flag);
}
/* Set up final interval. */
P_map = terminal_weights;
status_flag = qpDUNES_setupFinalInterval(&qp_data, qp_data.intervals[i],
P, g, zLow, zUpp, 0, 0, 0);
AssertOK(status_flag);
qpDUNES_setupAllLocalQPs(&qp_data, QPDUNES_FALSE);
qpDUNES_indicateDataChange(&qp_data);
}
