{"title":"基于遗忘因子递归最小二乘算法的机器人挖掘机识别模型","authors":"Hao Feng, C. Yin, Hongfu Yu, Donghui Cao","doi":"10.1109/ICACMVE.2019.00074","DOIUrl":null,"url":null,"abstract":"In order to establish the electro-hydraulic proportional system model of the robotic excavator quickly and accurately, an identification algorithm based on recursive least squares algorithm with forgetting factor is proposed. The basic the mathematical model of the electro-hydraulic proportional system are analyzed. Based on the theoretical models, the transfer function of the control system is obtained by recursive least square identification method. The improved recursive least squares algorithm with forgetting factor method overcomes the contradiction between the steady-state accuracy and tracking ability of the fixed forgetting factor algorithm, and makes the identification process have both higher dynamic response and higher identification accuracy. The experimental results show that the identification results are credible, which lays a foundation for system design, control characteristic analysis and intelligent control algorithm research.","PeriodicalId":375616,"journal":{"name":"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Robotic Excavator Identification Model Based on Recursive Least Squares Algorithm with Forgetting Factor\",\"authors\":\"Hao Feng, C. Yin, Hongfu Yu, Donghui Cao\",\"doi\":\"10.1109/ICACMVE.2019.00074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to establish the electro-hydraulic proportional system model of the robotic excavator quickly and accurately, an identification algorithm based on recursive least squares algorithm with forgetting factor is proposed. The basic the mathematical model of the electro-hydraulic proportional system are analyzed. Based on the theoretical models, the transfer function of the control system is obtained by recursive least square identification method. The improved recursive least squares algorithm with forgetting factor method overcomes the contradiction between the steady-state accuracy and tracking ability of the fixed forgetting factor algorithm, and makes the identification process have both higher dynamic response and higher identification accuracy. The experimental results show that the identification results are credible, which lays a foundation for system design, control characteristic analysis and intelligent control algorithm research.\",\"PeriodicalId\":375616,\"journal\":{\"name\":\"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACMVE.2019.00074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACMVE.2019.00074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robotic Excavator Identification Model Based on Recursive Least Squares Algorithm with Forgetting Factor
In order to establish the electro-hydraulic proportional system model of the robotic excavator quickly and accurately, an identification algorithm based on recursive least squares algorithm with forgetting factor is proposed. The basic the mathematical model of the electro-hydraulic proportional system are analyzed. Based on the theoretical models, the transfer function of the control system is obtained by recursive least square identification method. The improved recursive least squares algorithm with forgetting factor method overcomes the contradiction between the steady-state accuracy and tracking ability of the fixed forgetting factor algorithm, and makes the identification process have both higher dynamic response and higher identification accuracy. The experimental results show that the identification results are credible, which lays a foundation for system design, control characteristic analysis and intelligent control algorithm research.