基于改进粒子群算法的固定结构约束预览控制设计

N. Birla, A. Swarup
{"title":"基于改进粒子群算法的固定结构约束预览控制设计","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":"{\"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}","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

摘要

提出了一种基于协同进化粒子群优化和蜜蜂联姻优化算法的约束环境下多目标固定结构预瞄控制器的设计方法。本文还对进化算法中常用的约束处理方法与提出的混合多目标约束协同进化粒子群优化MOCC-PSO过程进行了比较评价。针对水下航行器和二自由度直升机的自主控制等工程设计问题,利用MATLAB平台对现有程序和算法进行了评估和验证。结果验证了该算法在约束环境下解的质量以及实现非经典目标和约束的便利性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Fixed structure constrained preview control design using enhanced PSO approach
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Path management strategy to reduce flooding of grid fisheye state routing protocol in mobile ad hoc network using fuzzy and rough set theory A novel cryptosystem based on cooperating distributed grammar systems Analysis of an M/G/1 retrial queue with Bernoulli vacation, two types of service and starting failure Array P system with t-communicating and permitting mate operation Two-dimensional double jumping finite automata
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1