{"title":"基于粒子群算法的航天器姿态机动自抗扰控制器参数优化","authors":"Ping Wang, Hua Wang, Guoyu Bai, Lin Su","doi":"10.1109/IHMSC.2014.149","DOIUrl":null,"url":null,"abstract":"In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.","PeriodicalId":370654,"journal":{"name":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parameter Optimization of ADRC for Spacecraft Attitude Maneuver Based on Particle Swarm Optimization Algorithm\",\"authors\":\"Ping Wang, Hua Wang, Guoyu Bai, Lin Su\",\"doi\":\"10.1109/IHMSC.2014.149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.\",\"PeriodicalId\":370654,\"journal\":{\"name\":\"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2014.149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2014.149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parameter Optimization of ADRC for Spacecraft Attitude Maneuver Based on Particle Swarm Optimization Algorithm
In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. Particle Swarm Optimization Algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.
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