Soft Computing Based Adaptive Error Optimisation for Control of Nonlinear System

Int. J. Energy Optim. Eng. Pub Date : 2017-07-01 DOI:10.4018/IJEOE.2017070104

Ashwani Kharola, P. Patil

{"title":"Soft Computing Based Adaptive Error Optimisation for Control of Nonlinear System","authors":"Ashwani Kharola, P. Patil","doi":"10.4018/IJEOE.2017070104","DOIUrl":null,"url":null,"abstract":"Thispaperelaboratesanovelhybridlearningapproachfortrainingerroroptimisationandcontrolof highlydynamictriple-linkinvertedpendulumoncart.Thestudydemonstratesarelationshipbetween shapeandnumberofmembershipfunctions(MFs)ofbothlinearandconstanttypetodetermine training error tolerance of ANFIS controller. The results are plotted which clearly highlighted supremacyofconstanttypethreetriangularshapeMFs.Mathematicalmodelandsimulinkofproposed systemhasalsobeenanalysed.Thelearningabilityanddesigningmethodologyofadaptivenetworks androbustnessofPIDcontrollersarebrieflydescribed.Finally,thestudyillustratesanofflinemode comparisonofPIDbasedANFISandNeuralcontrollersintermsofsettlingtime,steadystateerror andovershoot. KEywORdS ANFIS, Membership Functions, Neural Networks, PID, Simulation, Soft Computing, Training Error, TripleLink Pendulum","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"206 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Energy Optim. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJEOE.2017070104","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

Thispaperelaboratesanovelhybridlearningapproachfortrainingerroroptimisationandcontrolof highlydynamictriple-linkinvertedpendulumoncart.Thestudydemonstratesarelationshipbetween shapeandnumberofmembershipfunctions(MFs)ofbothlinearandconstanttypetodetermine training error tolerance of ANFIS controller. The results are plotted which clearly highlighted supremacyofconstanttypethreetriangularshapeMFs.Mathematicalmodelandsimulinkofproposed systemhasalsobeenanalysed.Thelearningabilityanddesigningmethodologyofadaptivenetworks androbustnessofPIDcontrollersarebrieflydescribed.Finally,thestudyillustratesanofflinemode comparisonofPIDbasedANFISandNeuralcontrollersintermsofsettlingtime,steadystateerror andovershoot. KEywORdS ANFIS, Membership Functions, Neural Networks, PID, Simulation, Soft Computing, Training Error, TripleLink Pendulum

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于软计算的非线性系统自适应误差优化控制

Thispaperelaboratesanovelhybridlearningapproachfortrainingerroroptimisationandcontrolof highlydynamictriple-linkinvertedpendulumoncart。Thestudydemonstratesarelationshipbetween shapeandnumberofmembershipfunctions(MFs)ofbothlinearandconstanttypetodetermine训练控制器的误差公差。结果被绘制出来，并被清晰地突出了supremacyofconstanttypethreetriangularshapeMFs。Mathematicalmodelandsimulinkofproposed systemhasalsobeenanalysed。Thelearningabilityanddesigningmethodologyofadaptivenetworks androbustnessofPIDcontrollersarebrieflydescribed。Finally，thestudyillustratesanofflinemode comparisonofPIDbasedANFISandNeuralcontrollersintermsofsettlingtime，steadystateerror andovershoot。关键词ANFIS，隶属函数，神经网络，PID，仿真，软计算，训练误差，三联摆

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Int. J. Energy Optim. Eng.

自引率

0.00%

发文量