Aleksandr P. Bondarchuk, P. V. Abramov, S. M. Bogdanova, D. Filatov
{"title":"移动机器人模型预测控制模型","authors":"Aleksandr P. Bondarchuk, P. V. Abramov, S. M. Bogdanova, D. Filatov","doi":"10.1109/scm55405.2022.9794835","DOIUrl":null,"url":null,"abstract":"The paper describes the approach to build a model predictive control system for a mobile robot with redundant architecture. In the paper we present a structure of such control system. This method is based on nonlinear models of kinematics and dynamics of the robot. A separate task is selection and adjustment of the optimal regulator. The proposed implementation combines the ideas of local planning and control of the actuators.","PeriodicalId":162457,"journal":{"name":"2022 XXV International Conference on Soft Computing and Measurements (SCM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobile Robot Model Predictive Control Model\",\"authors\":\"Aleksandr P. Bondarchuk, P. V. Abramov, S. M. Bogdanova, D. Filatov\",\"doi\":\"10.1109/scm55405.2022.9794835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes the approach to build a model predictive control system for a mobile robot with redundant architecture. In the paper we present a structure of such control system. This method is based on nonlinear models of kinematics and dynamics of the robot. A separate task is selection and adjustment of the optimal regulator. The proposed implementation combines the ideas of local planning and control of the actuators.\",\"PeriodicalId\":162457,\"journal\":{\"name\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/scm55405.2022.9794835\",\"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 XXV International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/scm55405.2022.9794835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper describes the approach to build a model predictive control system for a mobile robot with redundant architecture. In the paper we present a structure of such control system. This method is based on nonlinear models of kinematics and dynamics of the robot. A separate task is selection and adjustment of the optimal regulator. The proposed implementation combines the ideas of local planning and control of the actuators.
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