{"title":"非线性函数未知的Hammerstein系统的修正ESC","authors":"Y. Xie, Ruili Dong, Yonghong Tan","doi":"10.1109/YAC.2019.8787669","DOIUrl":null,"url":null,"abstract":"In this paper, a modified extreme seeking controller is designed for a Hammerstein system with unknown nonlinear function. In this Hammerstein system, only the model of linear subsystem is available. Therefore, the system is half transparent. Based on the available linear submodel, a predictor is developed and the steady state of system can be forecasted by the predictor. Then, a modified extreme seeking control (MESC) strategy based on the prediction result is applied to the control of Hammerstein systems. In the MESC, the technique of finite difference is implemented for estimating the gradients for searching the extremum of the system. Finally, simulation results are presented to show the validation the proposed method.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"1 1","pages":"504-508"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A modified ESC for Hammerstein systems with unknown nonlinear function\",\"authors\":\"Y. Xie, Ruili Dong, Yonghong Tan\",\"doi\":\"10.1109/YAC.2019.8787669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a modified extreme seeking controller is designed for a Hammerstein system with unknown nonlinear function. In this Hammerstein system, only the model of linear subsystem is available. Therefore, the system is half transparent. Based on the available linear submodel, a predictor is developed and the steady state of system can be forecasted by the predictor. Then, a modified extreme seeking control (MESC) strategy based on the prediction result is applied to the control of Hammerstein systems. In the MESC, the technique of finite difference is implemented for estimating the gradients for searching the extremum of the system. Finally, simulation results are presented to show the validation the proposed method.\",\"PeriodicalId\":6669,\"journal\":{\"name\":\"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"volume\":\"1 1\",\"pages\":\"504-508\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YAC.2019.8787669\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YAC.2019.8787669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A modified ESC for Hammerstein systems with unknown nonlinear function
In this paper, a modified extreme seeking controller is designed for a Hammerstein system with unknown nonlinear function. In this Hammerstein system, only the model of linear subsystem is available. Therefore, the system is half transparent. Based on the available linear submodel, a predictor is developed and the steady state of system can be forecasted by the predictor. Then, a modified extreme seeking control (MESC) strategy based on the prediction result is applied to the control of Hammerstein systems. In the MESC, the technique of finite difference is implemented for estimating the gradients for searching the extremum of the system. Finally, simulation results are presented to show the validation the proposed method.
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