{"title":"基于泰勒展开线性化的部分形式无模型自适应控制","authors":"Xiaolin Guo, R. Chi, Na Lin, Yang Liu","doi":"10.1109/ICIST55546.2022.9926850","DOIUrl":null,"url":null,"abstract":"In this paper, a Taylor expansion linearization-based partial-form model-free adaptive control (TELPF-MFAC) method is proposed, which provides a new way to solve complex nonlinear nonaffine systems. The unknown nonlinear nonaffine system is transformed into a new linear data model (LDM) with a nonlinear residual term. Unknown parameters in LDM are estimated by an adaptive updating mechanism. By utilizing ad-ditional control knowledge in both the control and the parameter updating law, the performance of the proposed method can be improved consequently. Simulation study shows the effectiveness of the proposed TELPF-MFAC.","PeriodicalId":211213,"journal":{"name":"2022 12th International Conference on Information Science and Technology (ICIST)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Taylor Expansion Linearization-Based Partial-Form Model-Free Adaptive Control\",\"authors\":\"Xiaolin Guo, R. Chi, Na Lin, Yang Liu\",\"doi\":\"10.1109/ICIST55546.2022.9926850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a Taylor expansion linearization-based partial-form model-free adaptive control (TELPF-MFAC) method is proposed, which provides a new way to solve complex nonlinear nonaffine systems. The unknown nonlinear nonaffine system is transformed into a new linear data model (LDM) with a nonlinear residual term. Unknown parameters in LDM are estimated by an adaptive updating mechanism. By utilizing ad-ditional control knowledge in both the control and the parameter updating law, the performance of the proposed method can be improved consequently. Simulation study shows the effectiveness of the proposed TELPF-MFAC.\",\"PeriodicalId\":211213,\"journal\":{\"name\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIST55546.2022.9926850\",\"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 12th International Conference on Information Science and Technology (ICIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST55546.2022.9926850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Taylor Expansion Linearization-Based Partial-Form Model-Free Adaptive Control
In this paper, a Taylor expansion linearization-based partial-form model-free adaptive control (TELPF-MFAC) method is proposed, which provides a new way to solve complex nonlinear nonaffine systems. The unknown nonlinear nonaffine system is transformed into a new linear data model (LDM) with a nonlinear residual term. Unknown parameters in LDM are estimated by an adaptive updating mechanism. By utilizing ad-ditional control knowledge in both the control and the parameter updating law, the performance of the proposed method can be improved consequently. Simulation study shows the effectiveness of the proposed TELPF-MFAC.