I’m having an issue where “PARTIAL_CONDENSING_HPIPM” and “FULL_CONDENSING_HPIPM” work nicely, but “FULL_CONDENSING_QPOASES” fails specifically in the presence of soft constraints. I’ve reduced the OCP to something very simple - linear dynamics, one state and one input variable, no nonlinear constraints, linear LS cost.

I’ve uploaded this example here:

Specifically, when constraints are softened (soft_constraints = True) and the number of time steps is large enough (N >= 12), FULL_CONDENSING_QPOASES does not converge and eventually (usually on the first or second iteration) throws Error 37 ‘RET_INIT_FAILED_INFEASIBILITY’. Everything works fine with hard constraints, so the OCP shouldn’t be infeasible.

Any idea what the problem might be? Thanks for your help!
Logan

Interestingly, qpOASES can return SUCCESS within 50 iterations on the first 4 problems, while taking 51 iterations when allowed more.
If anyone has some insight on this, I would be interested.

With qp_solver_iter_max=50, I got:

0
iter qp_stat qp_iter
0 0 0
1 0 0
1
solve time, 0.006324446999769862
iter qp_stat qp_iter
0 0 0
1 2 50
2
solve time, 0.0039940739998201025
iter qp_stat qp_iter
0 0 0
1 2 50
3
solve time, 0.003979571999934706
iter qp_stat qp_iter
0 0 0
1 2 50
4
solve time, 0.004307506999793986
iter qp_stat qp_iter
0 0 0
1 2 50
5
solve time, 0.0014888799996697344
Failed on instance 5 with status 4

while with qp_solver_iter_max=100, I get:

0
iter qp_stat qp_iter
0 0 0
1 0 0
1
solve time, 0.02731398499986426
iter qp_stat qp_iter
0 0 0
1 0 51
2
solve time, 0.0010279650000484253
iter qp_stat qp_iter
0 0 0
1 0 51
3
solve time, 0.004083296999851882
iter qp_stat qp_iter
0 0 0
1 0 51
4
solve time, 0.004239356999960364
iter qp_stat qp_iter
0 0 0
1 0 51
5
solve time, 0.0041367829999217065
iter qp_stat qp_iter
0 0 0
1 0 51