Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults
The reduced-order filtering problem for a class of discrete-time smooth nonlinear systems subject to multiple sensor faults is studied. It is well known that a smooth complex nonlinear system can be approximated by a Takagi-Sugeno fuzzy linear system with finite number of subsystems. In this work, f...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2013/676272 |
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doaj-213ad59bc5184fc2bd6aab519f2b4ae02020-11-24T23:22:37ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/676272676272Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor FaultsWenbai Li0Huxiong Li1College of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, Zhejiang 325035, ChinaOujiang College, Wenzhou University, Wenzhou, Zhejiang 325027, ChinaThe reduced-order filtering problem for a class of discrete-time smooth nonlinear systems subject to multiple sensor faults is studied. It is well known that a smooth complex nonlinear system can be approximated by a Takagi-Sugeno fuzzy linear system with finite number of subsystems. In this work, firstly, the discrete-time smooth nonlinear system is transferred into a Takagi-Sugeno fuzzy linear system with finite number of subsystems. Secondly, a filter with the reduced order of the original system is proposed to be designed. Different from the traditional assumption in which the measurement of the output is ideal, the measurement of the output is subject to sensor faults which are described via Bernoulli processes. By using the augmentation technique, a stochastic Takagi-Sugeno filtering error system is obtained. For the stochastic filtering error system, the exponential stability and the energy-to-peak performance are investigated. Sufficient conditions which can guarantee the exponential stability and the l2−l∞ performance are obtained. Then, with the proposed conditions, the design procedure of the filter for the nonlinear system is proposed. Finally, a numerical example is used to show the effectiveness of the proposed design methodology.http://dx.doi.org/10.1155/2013/676272 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wenbai Li Huxiong Li |
spellingShingle |
Wenbai Li Huxiong Li Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults Mathematical Problems in Engineering |
author_facet |
Wenbai Li Huxiong Li |
author_sort |
Wenbai Li |
title |
Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults |
title_short |
Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults |
title_full |
Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults |
title_fullStr |
Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults |
title_full_unstemmed |
Reduced-Order l2−l∞ Filter Design for a Class of Discrete-Time Nonlinear Systems with Multiple Sensor Faults |
title_sort |
reduced-order l2−l∞ filter design for a class of discrete-time nonlinear systems with multiple sensor faults |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
The reduced-order filtering problem for a class of discrete-time smooth nonlinear systems subject to multiple sensor faults is studied. It is well known that a smooth complex nonlinear system can be approximated by a Takagi-Sugeno fuzzy linear system with finite number of subsystems. In this work, firstly, the discrete-time smooth nonlinear system is transferred into a Takagi-Sugeno fuzzy linear system with finite number of subsystems. Secondly, a filter with the reduced order of the original system is proposed to be designed. Different from the traditional assumption in which the measurement of the output is ideal, the measurement of the output is subject to sensor faults which are described via Bernoulli processes. By using the augmentation technique, a stochastic Takagi-Sugeno filtering error system is obtained. For the stochastic filtering error system, the exponential stability and the energy-to-peak performance are investigated. Sufficient conditions which can guarantee the exponential stability and the l2−l∞ performance are obtained. Then, with the proposed conditions, the design procedure of the filter for the nonlinear system is proposed. Finally, a numerical example is used to show the effectiveness of the proposed design methodology. |
url |
http://dx.doi.org/10.1155/2013/676272 |
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