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Title: Output feedback Takagi-Sugeno fuzzy model predictive control through linear matrix inequalities approaches

Authors: Thalita B.S. Moreira; Marcus V.S. Costa; Fabricio G. Nogueira

Addresses: Federal Rural University of the Semi-Arid Region, Mossoró, RN, Brazil ' Federal Rural University of the Semi-Arid Region, Mossoró, RN, Brazil ' Federal University of Ceará, Fortaleza, CE, Brazil

Abstract: The present paper proposes an output feedback control scheme combining the Takagi-Sugeno (T-S) fuzzy method with a model predictive control (RMPC) technique, using parallel distributed compensation (PDC) and linear matrix inequalities (LMIs). The study presents an algorithm of relaxed RMPC, considering a nonlinear varying parameters rule-based T-S fuzzy model. Moreover, a new stability criterion is proposed considering an online observer-based output feedback T-S fuzzy model predictive control (FMPC). The aforementioned criterion is implemented through LMIs constraints ensuring the system's robust stability. This procedure assembles the aforementioned techniques and applies them in a benchmark problem. The obtained results evidence the better performance of the proposed method in comparison with the benchmark controller, considering analysis of time responses and performances indices.

Keywords: fuzzy control; model predictive control; FMPC; T-S fuzzy model; LMIs; output feedback control; robust stability criterion.

DOI: 10.1504/IJMIC.2022.10048794

International Journal of Modelling, Identification and Control, 2022 Vol.40 No.1, pp.84 - 91

Received: 22 Jan 2021
Accepted: 06 Jul 2021

Published online: 12 Jul 2022 *

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