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

Autor: Moreira, Thalita B.S., Costa, Marcus V.S., Nogueira, Fabricio G.
Zdroj: International Journal of Modelling, Identification and Control; 2022, Vol. 40 Issue: 1 p84-91, 8p
Abstrakt: 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.
Databáze: Supplemental Index