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Discrete Sliding-Mode Control for a Class of T-S Fuzzy Models with Modeling Error
Author(s) -
Hugang Han,
HakKeung Lam
Publication year - 2014
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2014.p0908
Subject(s) - control theory (sociology) , computer science , fuzzy logic , fuzzy control system , lyapunov function , lyapunov stability , sliding mode control , nonlinear system , controller (irrigation) , component (thermodynamics) , bounded function , norm (philosophy) , stability (learning theory) , variable structure control , mathematical optimization , control (management) , mathematics , artificial intelligence , machine learning , physics , quantum mechanics , mathematical analysis , law , political science , agronomy , biology , thermodynamics
This paper proposes a discrete sliding-mode controller for a class of nonlinear systems described by a T-S fuzzy model subject to modeling error, which may influence the system performance and the overall system stability. While most of existing literature treats the modeling error under the so-called parallel distributed compensation framework by using some norm-bounded matrices, the proposed control scheme in this paper integrates a feedback component, which mainly consists of fuzzy approximators to deal with the modeling error and an auxiliary component of the variable structure control with a sector to guarantee the global stability of the closed-loop system when the system state travels outside the sector. With the consideration of system stability, adaptive laws adjusting the parameters in the system are developed based on the Lyapunov synthesis approach. Finally, simulation results will confirm the effectiveness of the approach proposed in this paper.

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