JOURNAL ARTICLE

Adaptive fuzzy control of nonaffine nonlinear systems using Takagi-Sugeno fuzzy models

Abstract

We present a control method for a general nonlinear systems using Takagi-Sugeno fuzzy models and develop an adaptation law to adjust the parameters of the fuzzy system. It is proved that the closed-loop system is stable in the sense of Lyapunov and all signals including tracking error, fuzzy parameters and estimate of upper bound for approximation error are bounded. Finally, simulation results verify the effectiveness of the proposed control method.

Keywords:
Control theory (sociology) Fuzzy control system Fuzzy logic Nonlinear system Bounded function Tracking error Computer science Adaptive neuro fuzzy inference system Adaptive control Mathematics Approximation error Control (management) Mathematical optimization Artificial intelligence

Metrics

13
Cited By
1.92
FWCI (Field Weighted Citation Impact)
11
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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