JOURNAL ARTICLE

T-S Fuzzy Control for Uncertain Nonlinear Systems Using Adaptive Fuzzy Approach

Abstract

This paper proposes on-line modeling via Takagi-Sugeno (T-S) fuzzy models and robust adaptive control for a class of unknown nonlinear dynamic systems with external disturbances. The T-S fuzzy model is established to approximate an unknown nonlinear dynamic system in a linearized way. Fuzzy B-spline membership functions (BMFs) which possesses a fixed number of control points are developed for on-line tuning. In this paper, the closed-loop system which is controlled by the proposed controller can be stabilized and the tracking error will converge to zero. An example is simulated in order to confirm the effectiveness and applicability of the proposed methods in this paper.

Keywords:
Control theory (sociology) Nonlinear system Fuzzy logic Fuzzy control system Controller (irrigation) Adaptive control Computer science Adaptive neuro fuzzy inference system Spline (mechanical) Mathematics Mathematical optimization Control (management) Engineering Artificial intelligence

Metrics

10
Cited By
0.79
FWCI (Field Weighted Citation Impact)
25
Refs
0.80
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
Advanced Control Systems Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering

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