{"title":"基于观测器补偿器和rbfnn控制器的PMSLM跟踪控制策略","authors":"Zhentian Liu, Guangsen Wang, Zhiwei Wang","doi":"10.1109/DDCLS.2018.8515981","DOIUrl":null,"url":null,"abstract":"This paper is devoted to a high-precision tracking control strategy of permanent magnet synchronous linear motor (PMSLM). Firstly, the field-oriented control model of the PMSLM is established to calculate the electromagnetic thrust. To reconstruct the system states and reject the lump disturbance, a novel observer-based compensator is proposed, by taking the basic ideas of the frequency-domain disturbance observer and the time-domain one (the extended state observer in active disturbance rejection control, ADRC). A radial-basis-function neural network (RBFNN) controller with accurate approximation capability is utilized to tracking the desired motion trajectory. Contrasted to the RBFNN’s parameters self-evolved, a simple and unique parameters tuning method is derived to guarantee the compensator performance. All the proposed algorithms are implemented in a rapid control prototype (RCP) real-time simulation platform and the simulation and experiment results validate the rightness of theoretical analysis and the feasibility of the proposed methods.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"10 1","pages":"996-1000"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Tracking Control Strategy of PMSLM with A Novel Observer-based Compensator and A RBFNN-based Controller\",\"authors\":\"Zhentian Liu, Guangsen Wang, Zhiwei Wang\",\"doi\":\"10.1109/DDCLS.2018.8515981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is devoted to a high-precision tracking control strategy of permanent magnet synchronous linear motor (PMSLM). Firstly, the field-oriented control model of the PMSLM is established to calculate the electromagnetic thrust. To reconstruct the system states and reject the lump disturbance, a novel observer-based compensator is proposed, by taking the basic ideas of the frequency-domain disturbance observer and the time-domain one (the extended state observer in active disturbance rejection control, ADRC). A radial-basis-function neural network (RBFNN) controller with accurate approximation capability is utilized to tracking the desired motion trajectory. Contrasted to the RBFNN’s parameters self-evolved, a simple and unique parameters tuning method is derived to guarantee the compensator performance. All the proposed algorithms are implemented in a rapid control prototype (RCP) real-time simulation platform and the simulation and experiment results validate the rightness of theoretical analysis and the feasibility of the proposed methods.\",\"PeriodicalId\":6565,\"journal\":{\"name\":\"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"10 1\",\"pages\":\"996-1000\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS.2018.8515981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS.2018.8515981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tracking Control Strategy of PMSLM with A Novel Observer-based Compensator and A RBFNN-based Controller
This paper is devoted to a high-precision tracking control strategy of permanent magnet synchronous linear motor (PMSLM). Firstly, the field-oriented control model of the PMSLM is established to calculate the electromagnetic thrust. To reconstruct the system states and reject the lump disturbance, a novel observer-based compensator is proposed, by taking the basic ideas of the frequency-domain disturbance observer and the time-domain one (the extended state observer in active disturbance rejection control, ADRC). A radial-basis-function neural network (RBFNN) controller with accurate approximation capability is utilized to tracking the desired motion trajectory. Contrasted to the RBFNN’s parameters self-evolved, a simple and unique parameters tuning method is derived to guarantee the compensator performance. All the proposed algorithms are implemented in a rapid control prototype (RCP) real-time simulation platform and the simulation and experiment results validate the rightness of theoretical analysis and the feasibility of the proposed methods.