Maximal terminal region approach for MPC using subsets sequence

Abstract

For the sake of enlarging the domain of attraction of model predictive control (MPC), a novel approach of gradually approximating the maximal terminal state region is proposed in this paper. Given the terminal cost, both surrounding set sequence and subsets sequence of the maximal terminal region were constructed by employing one-step set expansion iteratively. It was theoretically proved that when the iteration time goes to infinity, both the surrounding set sequence and the subsets sequence will converge to the maximal terminal region. All surrounding and subsets sets in these sequences are extracted from the state space by exploiting support vector machine (SVM) classifier. Finally, simulations are implemented to validate the effectiveness of this approach.

Keywords

model predictive control (MPC) / terminal region / domain of attraction / support vector machine (SVM)

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Higher Education Press and Springer-Verlag Berlin Heidelberg