set_nl_cons¶
Class method.
-
do_mpc.estimator.MHE.
set_nl_cons
(self, expr_name, expr, ub=inf, soft_constraint=False, penalty_term_cons=1, maximum_violation=inf)¶ Introduce new constraint to the class. Further constraints are optional. Expressions must be formulated with respect to
_x
,_u
,_z
,_tvp
,_p
. They are implemented as:\[m(x,u,z,p_{\text{tv}}, p) \leq m_{\text{ub}}\]Setting the flag
soft_constraint=True
will introduce slack variables \(\epsilon\), such that:\[\begin{split}m(x,u,z,p_{\text{tv}}, p)-\epsilon &\leq m_{\text{ub}},\\ 0 &\leq \epsilon \leq \epsilon_{\text{max}},\end{split}\]Slack variables are added to the cost function and multiplied with the supplied penalty term. This formulation makes constraints soft, meaning that a certain violation is tolerated and does not lead to infeasibility. Typically, high values for the penalty are suggested to avoid significant violation of the constraints.
Parameters: - expr_name (string) – Arbitrary name for the given expression. Names are used for key word indexing.
- expr (CasADi SX or MX) – CasADi SX or MX function depending on
_x
,_u
,_z
,_tvp
,_p
.
Raises: - assertion – expr_name must be str
- assertion – expr must be a casadi SX or MX type
Returns: Returns the newly created expression. Expression can be used e.g. for the RHS.
Return type: casadi.SX
This page is auto-generated. Page source is not available on Github.