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Adaptive Fuzzy Control for Uncertain Nonlinear Systems with Time-delay

Wang Xin-jun

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Abstract

Based on relaxed stability conditions,the adaptive fuzzy control for nonlinear time-delay systems with unknown bounded uncertainties is studied in this paper.Three parameters are introduced into Lyapunov functional,the delay-dependent stability conditions with adjustable parameters are gotten.The observer-based adaptive fuzzy controller is design,observer gains and feedback gains can be gotten by solving a set of linear matrix inequalities(LMIs).When adjustable parameters taking different values,feedback gains and observer gains are also different,therefore,the dynamic performance of closed-loop systems can be optimized by taking proper adjustable parameters.Finally,an example is given to illustrate the effectiveness the proposed method.

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What this paper is about

Based on relaxed stability conditions,the adaptive fuzzy control for nonlinear time-delay systems with unknown bounded uncertainties is studied in this paper.Three parameters are introduced into Lyapunov functional,the delay-dependent stability conditions with adjustable parameters are gotten.The observer-based adaptive fuzzy controller is design,observer gains and feedback gains can be gotten by solving a set of linear matrix inequalities(LMIs).When adjustable parameters taking different values,feedback gains and observer gains are also different,therefore,the dynamic performance of closed-loop systems can be optimized by taking proper adjustable parameters.Finally,an example is given to illustrate the effectiveness the proposed method.

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Available abstract

Based on relaxed stability conditions,the adaptive fuzzy control for nonlinear time-delay systems with unknown bounded uncertainties is studied in this paper.Three parameters are introduced into Lyapunov functional,the delay-dependent stability conditions with adjustable parameters are gotten.The observer-based adaptive fuzzy controller is design,observer gains and feedback gains can be gotten by solving a set of linear matrix inequalities(LMIs).When adjustable parameters taking different values,feedback gains and observer gains are also different,therefore,the dynamic performance of closed-loop systems can be optimized by taking proper adjustable parameters.Finally,an example is given to illustrate the effectiveness the proposed method.

Key concepts: Control theory (sociology), Mathematics, Observer (physics), Fuzzy logic, Nonlinear system, Fuzzy control system, Stability (learning theory), Controller (irrigation)

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