A Semi-Continuous PWA Model Based Optimal Control Method for Nonlinear Systems

To alleviate the <i>mode</i> mismatch of multiple model methods for nonlinear systems when completely discrete dynamical equations are adopted, a semi-continuous piecewise affine (SCPWA) model based optimal control method is proposed. Firstly, a SCPWA model is constructed where <i>...

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Bibliographic Details
Main Authors: Xinjian Zhu, Chunyue Song, Jun Zhao, Zuhua Xu
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Processes
Subjects:
mpc
Online Access:https://www.mdpi.com/2227-9717/8/2/170
Description
Summary:To alleviate the <i>mode</i> mismatch of multiple model methods for nonlinear systems when completely discrete dynamical equations are adopted, a semi-continuous piecewise affine (SCPWA) model based optimal control method is proposed. Firstly, a SCPWA model is constructed where <i>modes</i> evolve in continuous time and continuous states evolve in discrete time. Thanks to this model, a piecewise affine (PWA) system can switch at any time instant whereas <i>mode</i> switching only occurs at sample instants when a completely discrete PWA model is adopted, which improves the prediction accuracy of multi-models. Secondly, the switching condition is relaxed such that operating subspaces have overlaps and switching condition parameters are introduced. As a consequence, an optimal control problem with fixed mode switching sequence is established. Finally, a SCPWA model based model predictive control (MPC) policy is designed for nonlinear systems. The convergence of the MPC algorithm is proved. Compared with widely used mixed logical dynamic (MLD) model based methods, the proposed method not only alleviates <i>mode</i> mismatch, but also lightens the computing burden, hence improves the control performance and reduces the computation time. Some numerical examples are provided as well to show the efficiency of the method.
ISSN:2227-9717