{"title":"基于lyapunov的遗传算法控制线性压电陶瓷电机驱动","authors":"R. Wai, Ching-Hsiang Tu, Zhiwei Yang","doi":"10.1109/ICCIS.2006.252231","DOIUrl":null,"url":null,"abstract":"This paper presents a Lyapunov-based genetic algorithm control (LGAC) system for a linear piezoelectric ceramic motor (LPCM) driven by a hybrid resonant inverter. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, an LGAC system via backstepping design technique is therefore investigated based on direction-based genetic algorithm to achieve high-precision position control. In this control scheme, a genetic algorithm (GA) control system is utilized to be the major controller, and adaptation laws derived from Lyapunov stability analyses are manipulated to adjust appropriate evolutionary steps. Moreover, the system stability can be guaranteed directly without strict constraint conditions and detailed system knowledge. In addition, the effectiveness of the proposed control system is verified by numerical simulations in the presence of uncertainties","PeriodicalId":296028,"journal":{"name":"2006 IEEE Conference on Cybernetics and Intelligent Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Lyapunov-based Genetic Algorithm Controlled Linear Piezoelectric Ceramic Motor Drive\",\"authors\":\"R. Wai, Ching-Hsiang Tu, Zhiwei Yang\",\"doi\":\"10.1109/ICCIS.2006.252231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Lyapunov-based genetic algorithm control (LGAC) system for a linear piezoelectric ceramic motor (LPCM) driven by a hybrid resonant inverter. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, an LGAC system via backstepping design technique is therefore investigated based on direction-based genetic algorithm to achieve high-precision position control. In this control scheme, a genetic algorithm (GA) control system is utilized to be the major controller, and adaptation laws derived from Lyapunov stability analyses are manipulated to adjust appropriate evolutionary steps. Moreover, the system stability can be guaranteed directly without strict constraint conditions and detailed system knowledge. In addition, the effectiveness of the proposed control system is verified by numerical simulations in the presence of uncertainties\",\"PeriodicalId\":296028,\"journal\":{\"name\":\"2006 IEEE Conference on Cybernetics and Intelligent Systems\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Conference on Cybernetics and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2006.252231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2006.252231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lyapunov-based Genetic Algorithm Controlled Linear Piezoelectric Ceramic Motor Drive
This paper presents a Lyapunov-based genetic algorithm control (LGAC) system for a linear piezoelectric ceramic motor (LPCM) driven by a hybrid resonant inverter. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, an LGAC system via backstepping design technique is therefore investigated based on direction-based genetic algorithm to achieve high-precision position control. In this control scheme, a genetic algorithm (GA) control system is utilized to be the major controller, and adaptation laws derived from Lyapunov stability analyses are manipulated to adjust appropriate evolutionary steps. Moreover, the system stability can be guaranteed directly without strict constraint conditions and detailed system knowledge. In addition, the effectiveness of the proposed control system is verified by numerical simulations in the presence of uncertainties