State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach
This paper discusses the linear parameter varying (LPV) gain scheduling control problem based on the Takagi-Sugeno (T-S) fuzzy linearization approach. Firstly, the affine nonlinear parameter varying (ANPV) description of a class of nonlinear dynamic processes is defined; that is, at any scheduling p...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2013/169454 |
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doaj-6960873a991949cdaf916c94f1de72012020-11-24T22:25:05ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/169454169454State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization ApproachJizhen Liu0Yang Hu1Zhongwei Lin2State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaThis paper discusses the linear parameter varying (LPV) gain scheduling control problem based on the Takagi-Sugeno (T-S) fuzzy linearization approach. Firstly, the affine nonlinear parameter varying (ANPV) description of a class of nonlinear dynamic processes is defined; that is, at any scheduling parameter, the corresponding system is affine nonlinear as usual. For such a class of ANPV systems, a kind of developed T-S fuzzy modeling procedure is proposed to deal with the nonlinearity, instead of the traditional Jacobian linearization approach. More concretely, the evaluation system for the approximation ability of the novelly developed T-S fuzzy modeling procedure is established. Consequently, the LPV T-S fuzzy system is obtained which can approximate the ANPV system with required accuracy. Secondly, the notion of piecewise parameter-dependent Lyapunov function is introduced, and then the stabilization problem and the state-feedback H∞ control problem of the LPV T-S fuzzy system are studied. The sufficient conditions are given in linear matrix inequalities (LMIs) form. Finally, a numerical example is provided to demonstrate the availability of the above approaches. The simulation results show the high approximation accuracy of the LPV T-S fuzzy system to the ANPV system and the effectiveness of the LPV T-S fuzzy gain scheduling control.http://dx.doi.org/10.1155/2013/169454 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jizhen Liu Yang Hu Zhongwei Lin |
spellingShingle |
Jizhen Liu Yang Hu Zhongwei Lin State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach Mathematical Problems in Engineering |
author_facet |
Jizhen Liu Yang Hu Zhongwei Lin |
author_sort |
Jizhen Liu |
title |
State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach |
title_short |
State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach |
title_full |
State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach |
title_fullStr |
State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach |
title_full_unstemmed |
State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach |
title_sort |
state-feedback h∞ control for lpv system using t-s fuzzy linearization approach |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
This paper discusses the linear parameter varying (LPV) gain scheduling control problem based on the Takagi-Sugeno (T-S) fuzzy linearization approach. Firstly, the affine nonlinear parameter
varying (ANPV) description of a class of nonlinear dynamic processes is defined; that is, at any scheduling parameter, the corresponding system is affine nonlinear as usual. For such a class of ANPV systems, a
kind of developed T-S fuzzy modeling procedure is proposed to deal with the nonlinearity, instead of the traditional Jacobian linearization approach. More concretely, the evaluation system for the approximation
ability of the novelly developed T-S fuzzy modeling procedure is established. Consequently, the LPV T-S fuzzy system is obtained which can approximate the ANPV system with required accuracy. Secondly, the notion of piecewise parameter-dependent Lyapunov function is introduced, and then the stabilization problem and the state-feedback H∞ control problem of the LPV T-S fuzzy system are studied. The sufficient conditions are given in linear matrix inequalities (LMIs) form. Finally, a numerical example is provided to demonstrate the availability of the above approaches. The simulation results show the high approximation accuracy of the LPV T-S fuzzy system to the ANPV system and the effectiveness of the LPV T-S fuzzy gain scheduling control. |
url |
http://dx.doi.org/10.1155/2013/169454 |
work_keys_str_mv |
AT jizhenliu statefeedbackhcontrolforlpvsystemusingtsfuzzylinearizationapproach AT yanghu statefeedbackhcontrolforlpvsystemusingtsfuzzylinearizationapproach AT zhongweilin statefeedbackhcontrolforlpvsystemusingtsfuzzylinearizationapproach |
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1725759496306819072 |