Efrain Mendez, Alexandro Ortiz, Pedro Ponce, Arturo Molina
{"title":"Electric machines control optimization by a novel geo-inspired earthquake metaheuristic algorithm","authors":"Efrain Mendez, Alexandro Ortiz, Pedro Ponce, Arturo Molina","doi":"10.1109/NANOFIM.2018.8688616","DOIUrl":null,"url":null,"abstract":"This paper presents a speed control of Direct Current (DC) motor with a Proportional-Integral-Derivative (PID) controller optimized by a new metaheuristic algorithm. A novel metaheuristic optimization method is proposed in this paper based on an earthquake as geology phenomenon. The Earthquake Algorithm (EA) is used to optimize both plant model and PID controller. Experimental results show a feasibility of the proposed method improving both the plant model and speed controller by PID. Besides, the implemented experimental control system proves that EA works in all different continuous nonlinear functions or engineering applications.","PeriodicalId":169865,"journal":{"name":"2018 Nanotechnology for Instrumentation and Measurement (NANOfIM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Nanotechnology for Instrumentation and Measurement (NANOfIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NANOFIM.2018.8688616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper presents a speed control of Direct Current (DC) motor with a Proportional-Integral-Derivative (PID) controller optimized by a new metaheuristic algorithm. A novel metaheuristic optimization method is proposed in this paper based on an earthquake as geology phenomenon. The Earthquake Algorithm (EA) is used to optimize both plant model and PID controller. Experimental results show a feasibility of the proposed method improving both the plant model and speed controller by PID. Besides, the implemented experimental control system proves that EA works in all different continuous nonlinear functions or engineering applications.