Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems
The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2015/856390 |
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| author | Sunjie Zhang Zidong Wang Jun Hu Jinling Liang Fuad E. Alsaadi |
| author_facet | Sunjie Zhang Zidong Wang Jun Hu Jinling Liang Fuad E. Alsaadi |
| author_sort | Sunjie Zhang |
| collection | DOAJ |
| description | The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out. |
| format | Article |
| id | doaj-art-7d331e6422a641718151fd098c80f08b |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-7d331e6422a641718151fd098c80f08b2025-02-03T05:57:34ZengWileyAbstract and Applied Analysis1085-33751687-04092015-01-01201510.1155/2015/856390856390Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked SystemsSunjie Zhang0Zidong Wang1Jun Hu2Jinling Liang3Fuad E. Alsaadi4School of Information Science and Technology, Donghua University, Shanghai 200051, ChinaDepartment of Computer Science, Brunel University, Uxbridge, Middlesex UB8 3PH, UKResearch Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, ChinaCommunication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi ArabiaCommunication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi ArabiaThe fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.http://dx.doi.org/10.1155/2015/856390 |
| spellingShingle | Sunjie Zhang Zidong Wang Jun Hu Jinling Liang Fuad E. Alsaadi Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems Abstract and Applied Analysis |
| title | Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems |
| title_full | Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems |
| title_fullStr | Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems |
| title_full_unstemmed | Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems |
| title_short | Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems |
| title_sort | analysis filtering and control for takagi sugeno fuzzy models in networked systems |
| url | http://dx.doi.org/10.1155/2015/856390 |
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