Basharat Ullah, S. Hussain, M. Yousuf, F. Khan, Sumeet Khalid, Siddique Akbar, Ali Muhammad
{"title":"用NARMA-L2控制器控制分励直流电动机速度","authors":"Basharat Ullah, S. Hussain, M. Yousuf, F. Khan, Sumeet Khalid, Siddique Akbar, Ali Muhammad","doi":"10.1109/ICT-PEP57242.2022.9988795","DOIUrl":null,"url":null,"abstract":"An Intelligent Neural Network (NN) based nonlinear Autoregressive-moving average (NARMA-L2) Controller is developed for speed control of separately excited D.C. Motor by performing the features of Artificial Neural Networks (ANN). The aim of the proposed approach is to improve tracking performance of separately excited D.C. motor as compared to the conventional (PI) control approach. Performance Comparison of SEDM for NARMA-L2 controller and the conventional PI controller is also discussed. The entire speed control mechanism for SEDM is modelled by using the MATLAB 8.0 toolbox. The intelligent NARMA-L2 controller is operated in two steps: - the first, the variations in external loads is performed to check the speed control performance of NARMA-L2. The second, the controller is operated at various reference speed. Simulation results shows the effectiveness, advantages and good performance of the NARMA-L2 which is described through the comparison of conventional PI controller and NARMA-L2 controller. Excellent results added to the simplicity of the drive system, makes the ANN based NARMA-L2 controller strategy very suitable for a wide range of applications such as industries, paper mills etc.","PeriodicalId":163424,"journal":{"name":"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Speed Control of Separately Excited DC Motor Using NARMA-L2 Controller\",\"authors\":\"Basharat Ullah, S. Hussain, M. Yousuf, F. Khan, Sumeet Khalid, Siddique Akbar, Ali Muhammad\",\"doi\":\"10.1109/ICT-PEP57242.2022.9988795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An Intelligent Neural Network (NN) based nonlinear Autoregressive-moving average (NARMA-L2) Controller is developed for speed control of separately excited D.C. Motor by performing the features of Artificial Neural Networks (ANN). The aim of the proposed approach is to improve tracking performance of separately excited D.C. motor as compared to the conventional (PI) control approach. Performance Comparison of SEDM for NARMA-L2 controller and the conventional PI controller is also discussed. The entire speed control mechanism for SEDM is modelled by using the MATLAB 8.0 toolbox. The intelligent NARMA-L2 controller is operated in two steps: - the first, the variations in external loads is performed to check the speed control performance of NARMA-L2. The second, the controller is operated at various reference speed. Simulation results shows the effectiveness, advantages and good performance of the NARMA-L2 which is described through the comparison of conventional PI controller and NARMA-L2 controller. Excellent results added to the simplicity of the drive system, makes the ANN based NARMA-L2 controller strategy very suitable for a wide range of applications such as industries, paper mills etc.\",\"PeriodicalId\":163424,\"journal\":{\"name\":\"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICT-PEP57242.2022.9988795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICT-PEP57242.2022.9988795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speed Control of Separately Excited DC Motor Using NARMA-L2 Controller
An Intelligent Neural Network (NN) based nonlinear Autoregressive-moving average (NARMA-L2) Controller is developed for speed control of separately excited D.C. Motor by performing the features of Artificial Neural Networks (ANN). The aim of the proposed approach is to improve tracking performance of separately excited D.C. motor as compared to the conventional (PI) control approach. Performance Comparison of SEDM for NARMA-L2 controller and the conventional PI controller is also discussed. The entire speed control mechanism for SEDM is modelled by using the MATLAB 8.0 toolbox. The intelligent NARMA-L2 controller is operated in two steps: - the first, the variations in external loads is performed to check the speed control performance of NARMA-L2. The second, the controller is operated at various reference speed. Simulation results shows the effectiveness, advantages and good performance of the NARMA-L2 which is described through the comparison of conventional PI controller and NARMA-L2 controller. Excellent results added to the simplicity of the drive system, makes the ANN based NARMA-L2 controller strategy very suitable for a wide range of applications such as industries, paper mills etc.