{"title":"On-Demand Type Feedback Controller by Implicit Self-Tuning Control","authors":"A. Yanou","doi":"10.1109/ICAMECHS.2018.8507136","DOIUrl":null,"url":null,"abstract":"This paper proposes a design method of on-demand type feedback controller based on generalized minimum variance control by using implicit self-tuning control. Coprime factorization approach can extend controller such as generalized minimum variance control (GMVC), generalized predictive control (GPC) and so on. The extended controller includes additional parameter, which can re-design the characteristic of the extended controller. On the other hand, the closed-loop characteristic by the extended controller maintains original one. Although strong stability systems can be obtained by the extended controller in order to design safe systems, focusing on feedback signal, the extended controller can also adjust the magnitude of the feedback signal. That is, the proposed controller can be designed so that the magnitude of the feedback signal becomes zero in the case that the control object is achieved. In other words the feedback signal by the proposed controller can appear on demand of achieving the control object. Therefore this paper proposes on-demand type feedback controller using implicit self-tuning control for plant uncertainty. A numerical example is shown in order to check the characteristic of the proposed method.","PeriodicalId":325361,"journal":{"name":"2018 International Conference on Advanced Mechatronic Systems (ICAMechS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Advanced Mechatronic Systems (ICAMechS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAMECHS.2018.8507136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a design method of on-demand type feedback controller based on generalized minimum variance control by using implicit self-tuning control. Coprime factorization approach can extend controller such as generalized minimum variance control (GMVC), generalized predictive control (GPC) and so on. The extended controller includes additional parameter, which can re-design the characteristic of the extended controller. On the other hand, the closed-loop characteristic by the extended controller maintains original one. Although strong stability systems can be obtained by the extended controller in order to design safe systems, focusing on feedback signal, the extended controller can also adjust the magnitude of the feedback signal. That is, the proposed controller can be designed so that the magnitude of the feedback signal becomes zero in the case that the control object is achieved. In other words the feedback signal by the proposed controller can appear on demand of achieving the control object. Therefore this paper proposes on-demand type feedback controller using implicit self-tuning control for plant uncertainty. A numerical example is shown in order to check the characteristic of the proposed method.