{"title":"具有加性时变时滞的不确定T-S模糊系统的时滞相关鲁棒镇定","authors":"Idrissi Said, E. Tissir, I. I. Boumhid","doi":"10.5875/ausmt.v7i2.1278","DOIUrl":null,"url":null,"abstract":"This paper investigates the problem of robust stabilization for uncertain Takagi–Sugeno (T–S) fuzzy systems with additive time varying delays. An appropriate Lyapunov-Krasovskii function is considered for solving this problem, and obtains considerably less conservative results than existing methods. The proposed approach constructs a new Lyapunov-Krasovskii functional using two additive delay components, and no free weighting matrices are employed in the theoretical result derivation. This reduces the number of scalar decision variables in linear matrix inequalities. The fuzzy state feedback gain is derived through the numerical solution of a set of linear matrix inequalities (LMIs). Finally, numerical examples are provided to illustrate the effectiveness of the proposed method, and to allow comparison with previous works.","PeriodicalId":38109,"journal":{"name":"International Journal of Automation and Smart Technology","volume":"7 1","pages":"71-78"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Delay-dependent Robust Stabilization for Uncertain T-S Fuzzy Systems with Additive Time Varying Delays\",\"authors\":\"Idrissi Said, E. Tissir, I. I. Boumhid\",\"doi\":\"10.5875/ausmt.v7i2.1278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the problem of robust stabilization for uncertain Takagi–Sugeno (T–S) fuzzy systems with additive time varying delays. An appropriate Lyapunov-Krasovskii function is considered for solving this problem, and obtains considerably less conservative results than existing methods. The proposed approach constructs a new Lyapunov-Krasovskii functional using two additive delay components, and no free weighting matrices are employed in the theoretical result derivation. This reduces the number of scalar decision variables in linear matrix inequalities. The fuzzy state feedback gain is derived through the numerical solution of a set of linear matrix inequalities (LMIs). Finally, numerical examples are provided to illustrate the effectiveness of the proposed method, and to allow comparison with previous works.\",\"PeriodicalId\":38109,\"journal\":{\"name\":\"International Journal of Automation and Smart Technology\",\"volume\":\"7 1\",\"pages\":\"71-78\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Automation and Smart Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5875/ausmt.v7i2.1278\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Automation and Smart Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5875/ausmt.v7i2.1278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Delay-dependent Robust Stabilization for Uncertain T-S Fuzzy Systems with Additive Time Varying Delays
This paper investigates the problem of robust stabilization for uncertain Takagi–Sugeno (T–S) fuzzy systems with additive time varying delays. An appropriate Lyapunov-Krasovskii function is considered for solving this problem, and obtains considerably less conservative results than existing methods. The proposed approach constructs a new Lyapunov-Krasovskii functional using two additive delay components, and no free weighting matrices are employed in the theoretical result derivation. This reduces the number of scalar decision variables in linear matrix inequalities. The fuzzy state feedback gain is derived through the numerical solution of a set of linear matrix inequalities (LMIs). Finally, numerical examples are provided to illustrate the effectiveness of the proposed method, and to allow comparison with previous works.
期刊介绍:
International Journal of Automation and Smart Technology (AUSMT) is a peer-reviewed, open-access journal devoted to publishing research papers in the fields of automation and smart technology. Currently, the journal is abstracted in Scopus, INSPEC and DOAJ (Directory of Open Access Journals). The research areas of the journal include but are not limited to the fields of mechatronics, automation, ambient Intelligence, sensor networks, human-computer interfaces, and robotics. These technologies should be developed with the major purpose to increase the quality of life as well as to work towards environmental, economic and social sustainability for future generations. AUSMT endeavors to provide a worldwide forum for the dynamic exchange of ideas and findings from research of different disciplines from around the world. Also, AUSMT actively seeks to encourage interaction and cooperation between academia and industry along the fields of automation and smart technology. For the aforementioned purposes, AUSMT maps out 5 areas of interests. Each of them represents a pillar for better future life: - Intelligent Automation Technology. - Ambient Intelligence, Context Awareness, and Sensor Networks. - Human-Computer Interface. - Optomechatronic Modules and Systems. - Robotics, Intelligent Devices and Systems.