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Decomposition based fuzzy model predictive control approaches for interconnected nonlinear systems

  • Latifa DalhoumiEmail author
  • Mohamed Chtourou
  • Mohamed Djemel
Research Article
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Abstract

This paper proposes fuzzy model predictive control (FMPC) strategies for nonlinear interconnected systems based mainly on a system decomposition approach. First, the Takagi-Sugeno (TS) fuzzy model is formulated in such a way to describe the behavior of the nonlinear system. Based on that description, a fuzzy model predictive control is determined. The system under consideration is decomposed into several subsystems. For each subsystem, the main idea consists of the decomposition of the control action into two parts: The decentralized part contains the parameters of the subsystem and the centralized part contains the elements of other subsystems. According to such decomposition, two strategies are defined aiming to circumvent the problems caused by interconnection between subsystems. The feasibility and efficiency of the proposed method are illustrated through numerical examples.

Keywords

Model predictive control centralized control decentralized control Takagi-Sugeno (TS) fuzzy models interconnected nonlinear systems fuzzy model predictive control parallel distributed compensation 
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Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Latifa Dalhoumi
    • 1
    Email author
  • Mohamed Chtourou
    • 1
  • Mohamed Djemel
    • 1
  1. 1.Control and Energy Management Laboratory (CEM-Lab), National School of Engineering of SfaxUniversity of SfaxSfaxTunisia

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