{"title":"Anthropomorphic Control over Electromechanical System Motion: Simulation and Implementation","authors":"V. Tyrva, A. Saushev, O. Shergina","doi":"10.1109/RusAutoCon49822.2020.9208070","DOIUrl":null,"url":null,"abstract":"The paper considers the methodological issues of anthropomorphic control over electromechanical system motion. The authors make a conclusion on the relevance of simulating technically feasible controls and the ‘man-machine’ system motions initiated by them, where an electromechanical system stands for ‘machine’. It has been shown that the mathematical formulation of the system control problem is to determine the control functions allowing for the achievement of the control goals set. Following the engineering psychology ideas, two interacting elements have been identified, i.e. the subject and the object, which are, respectively, the ‘man-operator’ and ‘machine’. They interact via Man-Machine Interface. It has been established that the anthropomorphic control model building principle determines the possibility of its technical implementation in an electromechanical system with manual, automatic, or joint (automated) control. The paper identifies specifics of technical implementation of the control effects on the system object using the new-type joint control mechanisms, the control elements of which ensure the data interaction between the man-operator and the system’s machine. For a verbal action pattern and the man-operator and machine responses used in engineering psychology the authors have developed the mathematical models of joint control over the system object that describe the control element motions. It has been shown that the man-operator retains the ability to correct the control considering the factors that, for various reasons, have not been considered in the mathematical model of the optimal control problem.","PeriodicalId":101834,"journal":{"name":"2020 International Russian Automation Conference (RusAutoCon)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Russian Automation Conference (RusAutoCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RusAutoCon49822.2020.9208070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The paper considers the methodological issues of anthropomorphic control over electromechanical system motion. The authors make a conclusion on the relevance of simulating technically feasible controls and the ‘man-machine’ system motions initiated by them, where an electromechanical system stands for ‘machine’. It has been shown that the mathematical formulation of the system control problem is to determine the control functions allowing for the achievement of the control goals set. Following the engineering psychology ideas, two interacting elements have been identified, i.e. the subject and the object, which are, respectively, the ‘man-operator’ and ‘machine’. They interact via Man-Machine Interface. It has been established that the anthropomorphic control model building principle determines the possibility of its technical implementation in an electromechanical system with manual, automatic, or joint (automated) control. The paper identifies specifics of technical implementation of the control effects on the system object using the new-type joint control mechanisms, the control elements of which ensure the data interaction between the man-operator and the system’s machine. For a verbal action pattern and the man-operator and machine responses used in engineering psychology the authors have developed the mathematical models of joint control over the system object that describe the control element motions. It has been shown that the man-operator retains the ability to correct the control considering the factors that, for various reasons, have not been considered in the mathematical model of the optimal control problem.