P. Evald, J. L. Mor, Romulo Thiago Silva da Rosa, R. Z. Azzolin, V. Oliveira, S. Botelho
{"title":"An extended Kalman filter state estimation-based robust MRAC for welding robot motor control","authors":"P. Evald, J. L. Mor, Romulo Thiago Silva da Rosa, R. Z. Azzolin, V. Oliveira, S. Botelho","doi":"10.1109/IECON.2017.8216501","DOIUrl":null,"url":null,"abstract":"The robotic welding processes have been highly widespread in manufacturing industries due to large-scale production. An area where these processes are widely applied are shipyards, where there are necessary hundreds to thousands of kilograms of weld by hour. However, systems that operate in open-air environments are vulnerable to sundry disturbances, noises in measures, as well as possible unavailability of measurement of some system states, required for the controller. Taking it into account, in this work, a Robust Model Reference Adaptive Control is proposed to regulate the velocity of a nonlinear motor of a linear welding robot. Furthermore, an Extended Kalman Filter is implemented to estimate the system states and attenuate measurement noises. The proposed control system demonstrated a very good performance with fast convergence and small error.","PeriodicalId":13098,"journal":{"name":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","volume":"125 1","pages":"2967-2972"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2017.8216501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The robotic welding processes have been highly widespread in manufacturing industries due to large-scale production. An area where these processes are widely applied are shipyards, where there are necessary hundreds to thousands of kilograms of weld by hour. However, systems that operate in open-air environments are vulnerable to sundry disturbances, noises in measures, as well as possible unavailability of measurement of some system states, required for the controller. Taking it into account, in this work, a Robust Model Reference Adaptive Control is proposed to regulate the velocity of a nonlinear motor of a linear welding robot. Furthermore, an Extended Kalman Filter is implemented to estimate the system states and attenuate measurement noises. The proposed control system demonstrated a very good performance with fast convergence and small error.