No State Constraints in Mpc Solver

[sichaozhang1112]

trafficstars

hello mpc.pytorch developer, first of all, mpc.pytorch is an amazing and fast mpc solver. however, i found there is no constraints for states for input of this mpc solver. although solving was fast, the solution did not satisfy state constraint conditions. did i miss this feature or it is just not developed yet? PS: the mpc expression in code does not include state constraints either

 min_{tau={x,u}} sum_t 0.5 tau_t^T C_t tau_t + c_t^T tau_t
                        s.t. x_{t+1} = f(x_t, u_t)
                            x_0 = x_init
                            u_lower <= u <= u_upper

sincerely asking, sichao

[bamos]

That's correct, we don't have general state constraints implemented

[sichaozhang1112]

That's correct, we don't have general state constraints implemented

thx for reply. i think i can try, if it will work, expressing x_k+1 in the form of ax_init+sum{b_iu_i}, therefore using control constraints to represent constraint of states.

[abdelhakim96]

Hi, @sichaozhang1112 Im interested in this feature as well! any progress in this regard?

[sichaozhang1112]

sorry, i did not continue this assumption but turned to build own optimization network. so, its feasibility still needs to be verified.