Dalhoumi Latifa, Chtourou Mohamed and Djemel Mohamed. Decomposition Based Fuzzy Model Predictive Control Approaches for Interconnected Nonlinear Systems. International Journal of Automation and Computing, vol. 16, no. 3, pp. 369-388, 2019. DOI: 10.1007/s11633-016-1021-3
Citation: Dalhoumi Latifa, Chtourou Mohamed and Djemel Mohamed. Decomposition Based Fuzzy Model Predictive Control Approaches for Interconnected Nonlinear Systems. International Journal of Automation and Computing, vol. 16, no. 3, pp. 369-388, 2019. DOI: 10.1007/s11633-016-1021-3

Decomposition Based Fuzzy Model Predictive Control Approaches for Interconnected Nonlinear Systems

  • 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 deflned aiming to circumvent the problems caused by interconnection between subsystems. The feasibility and e–ciency of the proposed method are illustrated through numerical examples.
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