{"title":"基于啁啾探测的pdes的规定时间极值搜索——第二部分:热PDE","authors":"C. Yilmaz, M. Krstić","doi":"10.23919/ACC53348.2022.9867441","DOIUrl":null,"url":null,"abstract":"We introduce a prescribed–time extremum seeking (PT-ES) design for a PDE-ODE cascade of a heat PDE feeding into an integrator, which in turn feeds into an unknown map. Leveraging the integrator in the PDE-ODE plant, and employing “chirpy” probing and demodulation signals designed by PDE motion planning methods, we achieve convergence to the extremum in a user-prescribed time independent of the distance of the initial estimate from the optimizer. Although this PDE-ODE cascade is defined on a fixed spatial domain, it is inspired by free boundary models such as the Stefan model of phase change dynamics. The design is based on the time-varying backstepping approach, which transforms the PDE-ODE cascade into a suitable prescribed-time stable target system, and the averaging-based estimations of the gradient as well as the Hessian of the map. By means of Lyapunov method, it is shown that the average closed-loop dynamics are prescribed-time stable. This Part II paper is companion to a Part I paper which introduces PT-ES for two problems that are less challenging than here: a static map and a map with an input delay.","PeriodicalId":366299,"journal":{"name":"2022 American Control Conference (ACC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prescribed-Time Extremum Seeking with Chirpy Probing for PDEs—Part II: Heat PDE\",\"authors\":\"C. Yilmaz, M. Krstić\",\"doi\":\"10.23919/ACC53348.2022.9867441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a prescribed–time extremum seeking (PT-ES) design for a PDE-ODE cascade of a heat PDE feeding into an integrator, which in turn feeds into an unknown map. Leveraging the integrator in the PDE-ODE plant, and employing “chirpy” probing and demodulation signals designed by PDE motion planning methods, we achieve convergence to the extremum in a user-prescribed time independent of the distance of the initial estimate from the optimizer. Although this PDE-ODE cascade is defined on a fixed spatial domain, it is inspired by free boundary models such as the Stefan model of phase change dynamics. The design is based on the time-varying backstepping approach, which transforms the PDE-ODE cascade into a suitable prescribed-time stable target system, and the averaging-based estimations of the gradient as well as the Hessian of the map. By means of Lyapunov method, it is shown that the average closed-loop dynamics are prescribed-time stable. This Part II paper is companion to a Part I paper which introduces PT-ES for two problems that are less challenging than here: a static map and a map with an input delay.\",\"PeriodicalId\":366299,\"journal\":{\"name\":\"2022 American Control Conference (ACC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ACC53348.2022.9867441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACC53348.2022.9867441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prescribed-Time Extremum Seeking with Chirpy Probing for PDEs—Part II: Heat PDE
We introduce a prescribed–time extremum seeking (PT-ES) design for a PDE-ODE cascade of a heat PDE feeding into an integrator, which in turn feeds into an unknown map. Leveraging the integrator in the PDE-ODE plant, and employing “chirpy” probing and demodulation signals designed by PDE motion planning methods, we achieve convergence to the extremum in a user-prescribed time independent of the distance of the initial estimate from the optimizer. Although this PDE-ODE cascade is defined on a fixed spatial domain, it is inspired by free boundary models such as the Stefan model of phase change dynamics. The design is based on the time-varying backstepping approach, which transforms the PDE-ODE cascade into a suitable prescribed-time stable target system, and the averaging-based estimations of the gradient as well as the Hessian of the map. By means of Lyapunov method, it is shown that the average closed-loop dynamics are prescribed-time stable. This Part II paper is companion to a Part I paper which introduces PT-ES for two problems that are less challenging than here: a static map and a map with an input delay.