Nobuaki Endo, T. Yoshimi, Koichiro Hayashi, H. Murakami
{"title":"模型预测控制在抛光机器人推推中的应用","authors":"Nobuaki Endo, T. Yoshimi, Koichiro Hayashi, H. Murakami","doi":"10.23919/ICCAS55662.2022.10003683","DOIUrl":null,"url":null,"abstract":"Much of the polishing work is done manually by skilled workers. It is not easy to teach robots to perform the detailed work of theirs and to conFigure and operate an appropriate control system to achieve this, and automation of this process has been delayed. Polishing is performed by pressing a rotating tool against the workpiece to be machined. To achieve this motion, PID control is used in the controllers of many robots. However, to determine the appropriate control gain, it is necessary to repeatedly adjust the control gain according to the processing target and processing conditions. The purpose of this research is to introduce Model Predictive Control (MPC) as a new control system for polishing robots. MPC is a control that predicts control output using a model of the control target. Therefore, we considered the target force value could be achieved without changing the MPC parameters when the force condition, a machining condition, is changed. In this paper, control block diagrams were created in MATLAB Simulink to apply MPC. The block diagram was then mounted on the actual machine to check whether it could be pressed with appropriate force, and the differences from PID were evaluated.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Model Predictive Control to Polishing Robot for Pushing Operation\",\"authors\":\"Nobuaki Endo, T. Yoshimi, Koichiro Hayashi, H. Murakami\",\"doi\":\"10.23919/ICCAS55662.2022.10003683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Much of the polishing work is done manually by skilled workers. It is not easy to teach robots to perform the detailed work of theirs and to conFigure and operate an appropriate control system to achieve this, and automation of this process has been delayed. Polishing is performed by pressing a rotating tool against the workpiece to be machined. To achieve this motion, PID control is used in the controllers of many robots. However, to determine the appropriate control gain, it is necessary to repeatedly adjust the control gain according to the processing target and processing conditions. The purpose of this research is to introduce Model Predictive Control (MPC) as a new control system for polishing robots. MPC is a control that predicts control output using a model of the control target. Therefore, we considered the target force value could be achieved without changing the MPC parameters when the force condition, a machining condition, is changed. In this paper, control block diagrams were created in MATLAB Simulink to apply MPC. The block diagram was then mounted on the actual machine to check whether it could be pressed with appropriate force, and the differences from PID were evaluated.\",\"PeriodicalId\":129856,\"journal\":{\"name\":\"2022 22nd International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 22nd International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICCAS55662.2022.10003683\",\"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 22nd International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS55662.2022.10003683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Model Predictive Control to Polishing Robot for Pushing Operation
Much of the polishing work is done manually by skilled workers. It is not easy to teach robots to perform the detailed work of theirs and to conFigure and operate an appropriate control system to achieve this, and automation of this process has been delayed. Polishing is performed by pressing a rotating tool against the workpiece to be machined. To achieve this motion, PID control is used in the controllers of many robots. However, to determine the appropriate control gain, it is necessary to repeatedly adjust the control gain according to the processing target and processing conditions. The purpose of this research is to introduce Model Predictive Control (MPC) as a new control system for polishing robots. MPC is a control that predicts control output using a model of the control target. Therefore, we considered the target force value could be achieved without changing the MPC parameters when the force condition, a machining condition, is changed. In this paper, control block diagrams were created in MATLAB Simulink to apply MPC. The block diagram was then mounted on the actual machine to check whether it could be pressed with appropriate force, and the differences from PID were evaluated.