Novel Separation Principle Based H\infty Observer-Controller Design for a Class of T-S Fuzzy Systems

The observer-based controller design for a T-S fuzzy system subject to external disturbance is investigated in this paper. First, an <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> observer is designed to estimate the unknown system s...

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Published inIEEE transactions on fuzzy systems Vol. 26; no. 6; pp. 3206 - 3221
Main Authors Xie, Wen-Bo, Wang, Yu-Long, Zhang, Jian, Fu, Ming-Yu
Format Journal Article
LanguageEnglish
Published IEEE 01.12.2018
Subjects
Control systems
Fuzzy systems
Indexes
Observer-based control
Observers
separation principle
Stability analysis
Takagi–Sugeno fuzzy system
Upper bound
Zirconium
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Abstract The observer-based controller design for a T-S fuzzy system subject to external disturbance is investigated in this paper. First, an <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> observer is designed to estimate the unknown system states, by a transformation process for system states and the disturbance term, a state feedback <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> controller is given. Then, the separation principle for a T-S fuzzy system subject to external disturbance is proposed. With the help of the improved separation principle, the observer and controller can be combined together to make the fuzzy system input-state stable, while the <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> index can also be guaranteed. The proposed design approach is applicable for both known and unknown premise variables. In stability analysis, the membership functions derivatives dependent method is proposed to reduce the conservatism. In the simulation part, stability analysis of a three-rule system is carried out to illustrate the conservatism reduction effects in Example <xref ref-type="example" rid="example1">1 ; then, a vessel dynamic positioning control process subject to ocean disturbance is adopted to illustrate the effectiveness of the proposed methods for both known/unknown premise variable cases.
AbstractList The observer-based controller design for a T-S fuzzy system subject to external disturbance is investigated in this paper. First, an <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> observer is designed to estimate the unknown system states, by a transformation process for system states and the disturbance term, a state feedback <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> controller is given. Then, the separation principle for a T-S fuzzy system subject to external disturbance is proposed. With the help of the improved separation principle, the observer and controller can be combined together to make the fuzzy system input-state stable, while the <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> index can also be guaranteed. The proposed design approach is applicable for both known and unknown premise variables. In stability analysis, the membership functions derivatives dependent method is proposed to reduce the conservatism. In the simulation part, stability analysis of a three-rule system is carried out to illustrate the conservatism reduction effects in Example <xref ref-type="example" rid="example1">1 ; then, a vessel dynamic positioning control process subject to ocean disturbance is adopted to illustrate the effectiveness of the proposed methods for both known/unknown premise variable cases.
Author Zhang, Jian
Xie, Wen-Bo
Fu, Ming-Yu
Wang, Yu-Long
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Snippet The observer-based controller design for a T-S fuzzy system subject to external disturbance is investigated in this paper. First, an <inline-formula><tex-math...
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SubjectTerms Control systems
Fuzzy systems
Indexes
Observer-based control
Observers
separation principle
Stability analysis
Takagi–Sugeno fuzzy system
Upper bound
Zirconium
Title Novel Separation Principle Based H\infty Observer-Controller Design for a Class of T-S Fuzzy Systems
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