{"title":"移动摆机器人优化PID与模糊控制策略的比较","authors":"Á. Odry, R. Fuller","doi":"10.1109/SACI.2018.8440947","DOIUrl":null,"url":null,"abstract":"S-This paper investigates the optimized control performances of fuzzy and proportional-integral-derivative (PID) control schemes developed for the stabilization of an under-actuated mobile robot. The fuzzy control strategy had been designed in an earlier paper, its equivalent PID controller-based scheme is established first. Then a complex cost function is defined that evaluates the reference tracking performance, the efficiency of system oscillations suppression and the average current consumption in the motor drive system. The particle swarm optimization (PSO) is applied to tune both control schemes under the same circumstances by minimizing the formulated cost function. Results demonstrate that the optimized fuzzy control strategy provides the same reference tracking quality with significantly better suppression of system oscillations and current peaks compared to the optimized PID control.","PeriodicalId":126087,"journal":{"name":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Comparison of Optimized PID and Fuzzy Control Strategies on a Mobile Pendulum Robot\",\"authors\":\"Á. Odry, R. Fuller\",\"doi\":\"10.1109/SACI.2018.8440947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"S-This paper investigates the optimized control performances of fuzzy and proportional-integral-derivative (PID) control schemes developed for the stabilization of an under-actuated mobile robot. The fuzzy control strategy had been designed in an earlier paper, its equivalent PID controller-based scheme is established first. Then a complex cost function is defined that evaluates the reference tracking performance, the efficiency of system oscillations suppression and the average current consumption in the motor drive system. The particle swarm optimization (PSO) is applied to tune both control schemes under the same circumstances by minimizing the formulated cost function. Results demonstrate that the optimized fuzzy control strategy provides the same reference tracking quality with significantly better suppression of system oscillations and current peaks compared to the optimized PID control.\",\"PeriodicalId\":126087,\"journal\":{\"name\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2018.8440947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2018.8440947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Optimized PID and Fuzzy Control Strategies on a Mobile Pendulum Robot
S-This paper investigates the optimized control performances of fuzzy and proportional-integral-derivative (PID) control schemes developed for the stabilization of an under-actuated mobile robot. The fuzzy control strategy had been designed in an earlier paper, its equivalent PID controller-based scheme is established first. Then a complex cost function is defined that evaluates the reference tracking performance, the efficiency of system oscillations suppression and the average current consumption in the motor drive system. The particle swarm optimization (PSO) is applied to tune both control schemes under the same circumstances by minimizing the formulated cost function. Results demonstrate that the optimized fuzzy control strategy provides the same reference tracking quality with significantly better suppression of system oscillations and current peaks compared to the optimized PID control.