参数值和噪声对基于pso的预测控制影响的实证研究

Computational Intelligence in Control and Automation (CICA) Pub Date : 2011-04-11 DOI:10.1109/CICA.2011.5945743

M. Yousuf, H. Al-Duwaish

{"title":"参数值和噪声对基于pso的预测控制影响的实证研究","authors":"M. Yousuf, H. Al-Duwaish","doi":"10.1109/CICA.2011.5945743","DOIUrl":null,"url":null,"abstract":"In this paper, a Particle Swarm Optimization (PSO) based Model Predictive Control (MPC) scheme is studied through a variety of tests to better understand its behavior and characteristics. The technique has already been presented in the literature. Here, the PSO and MPC parameters are varied to study the effects on the quality of control and system dynamics. Model mismatch and noise are also introduced to test the controller performance. The results from various tests are compared and conclusions are drawn.","PeriodicalId":420555,"journal":{"name":"Computational Intelligence in Control and Automation (CICA)","volume":"629 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Effects of parameter values and noise on PSO-based predictive control: An empirical study\",\"authors\":\"M. Yousuf, H. Al-Duwaish\",\"doi\":\"10.1109/CICA.2011.5945743\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a Particle Swarm Optimization (PSO) based Model Predictive Control (MPC) scheme is studied through a variety of tests to better understand its behavior and characteristics. The technique has already been presented in the literature. Here, the PSO and MPC parameters are varied to study the effects on the quality of control and system dynamics. Model mismatch and noise are also introduced to test the controller performance. The results from various tests are compared and conclusions are drawn.\",\"PeriodicalId\":420555,\"journal\":{\"name\":\"Computational Intelligence in Control and Automation (CICA)\",\"volume\":\"629 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Intelligence in Control and Automation (CICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICA.2011.5945743\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Intelligence in Control and Automation (CICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICA.2011.5945743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

本文研究了一种基于粒子群优化(PSO)的模型预测控制(MPC)方案，并通过多种试验了解了其行为和特性。该技术已经在文献中提出。在这里，改变PSO和MPC参数来研究对控制质量和系统动力学的影响。同时引入模型失配和噪声来测试控制器的性能。对各种试验结果进行了比较，得出了结论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Effects of parameter values and noise on PSO-based predictive control: An empirical study

In this paper, a Particle Swarm Optimization (PSO) based Model Predictive Control (MPC) scheme is studied through a variety of tests to better understand its behavior and characteristics. The technique has already been presented in the literature. Here, the PSO and MPC parameters are varied to study the effects on the quality of control and system dynamics. Model mismatch and noise are also introduced to test the controller performance. The results from various tests are compared and conclusions are drawn.

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

Computational Intelligence in Control and Automation (CICA)

自引率

0.00%

发文量