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Indirect adaptive fuzzy control of nonlinear descriptor systems

Authors :
Luigi Chisci
Ali Akbarzadeh Kalat
Naeimeh Fakhr Shamloo
Source :
European Journal of Control. 51:30-38
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

This paper focuses on indirect adaptive fuzzy control of nonlinear descriptor systems described by both uncertain algebraic and differential equations aiming to guarantee asymptotic tracking of a regular and impulse-free descriptor reference model. The proposed controller exploits the universal approximation capability of Takagi–Sugeno–Kang (TSK) fuzzy models for the identification of the unknown system dynamics. More specifically, it is assumed that only the system order is known while all the dynamical equations of the system are completely unknown. In the proposed method, the asymptotic tracking of the reference model is guaranteed by suitable adaptation laws for the parameters of the TSK fuzzy model. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Details

ISSN :
09473580
Volume :
51
Database :
OpenAIRE
Journal :
European Journal of Control
Accession number :
edsair.doi...........6ddd8e8c9195633db208ebe8aab1157f
Full Text :
https://doi.org/10.1016/j.ejcon.2019.06.007