Minimization of cost function on MPC
조회 수: 24(최근 30일)
I want to optimize a cost function of MPC which is output reference tracking as shown below:
min J(∆u) = ||xref(k + i) − x(k + i)||2 Q+ ||∆u(k + i)||2 R + ||xref(k + N) − x(k + N)||2 S, where Q,R and S are weight matrices.
Can anyone tell me how can I optimize this with constraint -1<∆u<1. Is it better use solver or can I optimize it without using solver?
If using solver, how can I convert into standard solver form?
If without using solver, which function to be used to minimize this cost function?
Any help is appreciated. Thanks in advance
Sam Chak 2022년 11월 7일
You have a system model sys and I presume that you have written your own code for the ODE_solver to run the sys.
Under normal circumstances, you should be able to specify the initial states y0 in the ODE_solver.
The solver should produce the numerical solution array y that corresponds to a value returned in time vector t.
With the data, you can run your own optim_solver to produce some control action u.
Then, update the initial states y0 with final value of the states y(end) from the last iteration.
Finally, repeat the loop/steps by running the ODE_solver > the optim_solver until the specified number of iteration is completed.