{"title":"Fixed structure constrained preview control design using enhanced PSO approach","authors":"N. Birla, A. Swarup","doi":"10.1504/IJAISC.2014.062828","DOIUrl":null,"url":null,"abstract":"This paper proposes the design of fixed structure preview controller with multiple objectives in constrained environment using hybrid technique based on co-evolutionary particle swarm optimisation and marriage in honey bees optimisation algorithm. The paper, also, presents a comparative evaluation of the commonly used constraint - handling approaches in evolutionary algorithms with the proposed hybrid multi-objective constrained co-evolutionary particle swarm optimisation MOCC-PSO procedure. The available procedures and the proposed algorithm are evaluated and verified using MATLAB platform for engineering design problems, namely autonomous control of under-water vehicle and 2-DOF helicopter. The results validate the ability of the algorithm in terms of the quality of solution obtained in the constrained environment and the ease to implement the non-classical objectives and constraints.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Artif. Intell. Soft Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJAISC.2014.062828","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
This paper proposes the design of fixed structure preview controller with multiple objectives in constrained environment using hybrid technique based on co-evolutionary particle swarm optimisation and marriage in honey bees optimisation algorithm. The paper, also, presents a comparative evaluation of the commonly used constraint - handling approaches in evolutionary algorithms with the proposed hybrid multi-objective constrained co-evolutionary particle swarm optimisation MOCC-PSO procedure. The available procedures and the proposed algorithm are evaluated and verified using MATLAB platform for engineering design problems, namely autonomous control of under-water vehicle and 2-DOF helicopter. The results validate the ability of the algorithm in terms of the quality of solution obtained in the constrained environment and the ease to implement the non-classical objectives and constraints.