{"title":"基于Lyapunov方法的小波神经网络自整定PID设计","authors":"M. Farahani, S. Ganjefar, M. Alizadeh","doi":"10.1109/ICCIAUTOM.2011.6356671","DOIUrl":null,"url":null,"abstract":"This paper presents an adaptive self-tuning PID controller based on the Lyapunov method. To tune the gains of PID controller, a self-tuning algorithm derived by the Lyapunov method is employed. Hence, the control error converges to zero and the stability of the controlled system is guaranteed. To accommodate the controller, the wavelet neural network (WNN) is used. The simulation results are used to demonstrate the effectiveness of designed controller. With the proposed controller, the controlled system possesses the advantages of good tracking control performance and robustness to unknown process.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A self-tuning PID design based on wavelet neural network using Lyapunov method\",\"authors\":\"M. Farahani, S. Ganjefar, M. Alizadeh\",\"doi\":\"10.1109/ICCIAUTOM.2011.6356671\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an adaptive self-tuning PID controller based on the Lyapunov method. To tune the gains of PID controller, a self-tuning algorithm derived by the Lyapunov method is employed. Hence, the control error converges to zero and the stability of the controlled system is guaranteed. To accommodate the controller, the wavelet neural network (WNN) is used. The simulation results are used to demonstrate the effectiveness of designed controller. With the proposed controller, the controlled system possesses the advantages of good tracking control performance and robustness to unknown process.\",\"PeriodicalId\":438427,\"journal\":{\"name\":\"The 2nd International Conference on Control, Instrumentation and Automation\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd International Conference on Control, Instrumentation and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIAUTOM.2011.6356671\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd International Conference on Control, Instrumentation and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2011.6356671","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A self-tuning PID design based on wavelet neural network using Lyapunov method
This paper presents an adaptive self-tuning PID controller based on the Lyapunov method. To tune the gains of PID controller, a self-tuning algorithm derived by the Lyapunov method is employed. Hence, the control error converges to zero and the stability of the controlled system is guaranteed. To accommodate the controller, the wavelet neural network (WNN) is used. The simulation results are used to demonstrate the effectiveness of designed controller. With the proposed controller, the controlled system possesses the advantages of good tracking control performance and robustness to unknown process.