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Close: #336
The current implementation concatenates the inequality/equality(the upper part) and the loss function([loss_bc; loss_collocation] as the lower part) as the constraints in OptimizationProblem. The Jacobian is handled by concatenating the Jacobian of inequality constraints(the upper square matrix) and the Jacobian of the loss function ([jac_loss_bc; jac_loss_collocation] as the lower rectangular matrix), resulting in a
(N*M + length(bc_resid_prototype) + length(f_prototype)*(N-1)) x (N*M)Jacobian. Then the Jacobian is, upper part: banded matrix; lower part: almost banded matrix.There are some weird issues with formulating the state variables and control variables, which may prevent the solver from finding an optimal solution. I’ll see what’s going wrong here.
Some TODOs:
uconsandlconshandling. More friendly information on choosinguconsandlconsshould be provided to users.