Enlarging the Terminal Region of NMPC with Parameter-Dependent Terminal Control Law
Nominal stability of a quasi-infinite horizon nonlinear model predictive control (QIH-NMPC) scheme is obtained by an appropriate choice of the terminal region and the terminal penalty term. This paper presents a new method to enlarge the terminal region, and therefore the domain of attraction of the QIH-NMPC scheme. The proposed method applies a parameter-dependent terminal controller. The problem of maximizing the terminal region is formulated as a convex optimization problem based on linear matrix inequalities. Compared to existing methods using a linear time-invariant terminal controller, the presented approach may enlarge the terminal region significantly. This is confirmed via simulations of an example system.
KeywordsNonlinear Model predictive control Terminal invariant sets Linear differential inclusion Linear matrix inequality
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