{"title":"Self-Tuning PID Controller Based on Quantum Swarm Evolution Algorithm","authors":"Yourui Huang, Liguo Qu, Yiming Tian","doi":"10.1109/ICNC.2008.458","DOIUrl":null,"url":null,"abstract":"PID control schemes have been widely used in most of control system for a long time. However, it is still a very important problem how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. On the other hand, in the last ten years, quantum computing is attracted as one method which gives us suitable answers for optimization problems. This paper proposes a novel quantum swarm evolution algorithm, called a quantum-inspired swarm evolution algorithm (QSEA), which is based on the concept and principles of quantum computing. The proposed algorithm adopts quantum angle to express Q-bit and improved particle swarm optimization to update automatically. After the quantum-inspired swarm evolution algorithm is described, the experiment result on the parameters of PID controller is given to show its efficiency.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"15 1","pages":"401-404"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Fourth International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2008.458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
PID control schemes have been widely used in most of control system for a long time. However, it is still a very important problem how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. On the other hand, in the last ten years, quantum computing is attracted as one method which gives us suitable answers for optimization problems. This paper proposes a novel quantum swarm evolution algorithm, called a quantum-inspired swarm evolution algorithm (QSEA), which is based on the concept and principles of quantum computing. The proposed algorithm adopts quantum angle to express Q-bit and improved particle swarm optimization to update automatically. After the quantum-inspired swarm evolution algorithm is described, the experiment result on the parameters of PID controller is given to show its efficiency.