Adaptive fuzzy nonlinear inversion-based control for uncertain chaotic systems

This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state...

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Bibliographic Details
Published inChinese physics B Vol. 21; no. 12; pp. 123 - 129
Main Author 刘恒 余海军 向伟
Format Journal Article
LanguageEnglish
Published 01.12.2012
Subjects
Chaos theory
Control systems
Controllers
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy systems
Lyapunov
Nonlinearity
Stability analysis
不确定混沌系统
基础
模糊系统
自适应
输出反馈控制
非线性函数
非线性反演
Online AccessGet full text
ISSN1674-1056
2058-3834
1741-4199
DOI10.1088/1674-1056/21/12/120505

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Summary:This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.
Bibliography:This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.
chaotic systems, nonlinear inversion-based control, adaptive fuzzy control, variable struc- ture control
11-5639/O4
Liu Heng, Yu Hai-Jun, and Xiang Wei a） School of Mathematics and Computer Science, Huainan Normal University, Huainan 232038, China b） School of Physics and Electronic Information, Huainan Normal University, Huainan 232038, China
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ISSN:1674-1056
2058-3834
1741-4199
DOI:10.1088/1674-1056/21/12/120505