{"title":"多参数ESA优化反演控制","authors":"Weijie Dong, Yun-an Hu, Bin Zuo, Wanli Dong","doi":"10.1109/ICAIE.2010.5641411","DOIUrl":null,"url":null,"abstract":"For the case that the traditional parameter adjustment consumes too much time, a method using the multi-parameter extremum seeking algorithm (m-p ESA) to tune the backstepping controller parameters is presented. The m-p ESA can obtain the optimized value of parameters by minimizing the cost function to achieve the desired performance and avoid the interaction of parameters by the multiple channels design. Therefore the utilization of the m-p ESA can simplify the process of parameter adjustment. In addition, the stability is analyzed by Lyapunov theory The simulation results demonstrate the backstepping controller optimized by the m-p ESA is effective.","PeriodicalId":216006,"journal":{"name":"2010 International Conference on Artificial Intelligence and Education (ICAIE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Backstepping control optimized by the multi-parameter ESA\",\"authors\":\"Weijie Dong, Yun-an Hu, Bin Zuo, Wanli Dong\",\"doi\":\"10.1109/ICAIE.2010.5641411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the case that the traditional parameter adjustment consumes too much time, a method using the multi-parameter extremum seeking algorithm (m-p ESA) to tune the backstepping controller parameters is presented. The m-p ESA can obtain the optimized value of parameters by minimizing the cost function to achieve the desired performance and avoid the interaction of parameters by the multiple channels design. Therefore the utilization of the m-p ESA can simplify the process of parameter adjustment. In addition, the stability is analyzed by Lyapunov theory The simulation results demonstrate the backstepping controller optimized by the m-p ESA is effective.\",\"PeriodicalId\":216006,\"journal\":{\"name\":\"2010 International Conference on Artificial Intelligence and Education (ICAIE)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Artificial Intelligence and Education (ICAIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIE.2010.5641411\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Artificial Intelligence and Education (ICAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIE.2010.5641411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Backstepping control optimized by the multi-parameter ESA
For the case that the traditional parameter adjustment consumes too much time, a method using the multi-parameter extremum seeking algorithm (m-p ESA) to tune the backstepping controller parameters is presented. The m-p ESA can obtain the optimized value of parameters by minimizing the cost function to achieve the desired performance and avoid the interaction of parameters by the multiple channels design. Therefore the utilization of the m-p ESA can simplify the process of parameter adjustment. In addition, the stability is analyzed by Lyapunov theory The simulation results demonstrate the backstepping controller optimized by the m-p ESA is effective.