solve

Class method.

do_mpc.estimator.MHE.solve(self)

Solves the optmization problem.

The current problem is defined by the parameters in the opt_p_num CasADi structured Data.

Typically, opt_p_num is prepared for the current iteration in the make_step() method. It is, however, valid and possible to directly set paramters in opt_p_num before calling solve().

The method updates the opt_p_num and opt_x_num attributes of the class. By resetting opt_x_num to the current solution, the method implicitly enables warmstarting the optimizer for the next iteration, since this vector is always used as the initial guess.

Warning

The method is part of the public API but it is generally not advised to use it. Instead we recommend to call make_step() at each iterations, which acts as a wrapper for solve().

Raises:asssertion – Optimizer was not setup yet.
Returns:None
Return type:None

This page is auto-generated. Page source is not available on Github.