The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing...The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adap-tiveness and fast responding features.The Model Predictive Control(MPC)tech-nique is a widely used,safe and reliable control method based on constraints.On the other hand,the Eddy Current dynamometers are highly nonlinear braking sys-tems whose performance parameters are related to many processes related vari-ables.This study is based on an adaptive model predictive control that utilizes selected AI methods.The presented approach presents an updated the mathema-tical model of an Eddy Current Dynamometer based on experimentally obtained system operational data.Finally,the comparison of AI methods and related learn-ing performances based on the assessment technique of mean absolute percentage error(MAPE)issues are discussed.The results indicate that Single Hidden Layer Neural Network(SHLNN),General Regression Neural Network(GRNN),Radial Basis Network(RBNN),Neuro Fuzzy Network(ANFIS)coupled MPC have quite satisfying performances.The presented results indicate that,amongst them,GRNN appears to provide the best performance.展开更多
文摘The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adap-tiveness and fast responding features.The Model Predictive Control(MPC)tech-nique is a widely used,safe and reliable control method based on constraints.On the other hand,the Eddy Current dynamometers are highly nonlinear braking sys-tems whose performance parameters are related to many processes related vari-ables.This study is based on an adaptive model predictive control that utilizes selected AI methods.The presented approach presents an updated the mathema-tical model of an Eddy Current Dynamometer based on experimentally obtained system operational data.Finally,the comparison of AI methods and related learn-ing performances based on the assessment technique of mean absolute percentage error(MAPE)issues are discussed.The results indicate that Single Hidden Layer Neural Network(SHLNN),General Regression Neural Network(GRNN),Radial Basis Network(RBNN),Neuro Fuzzy Network(ANFIS)coupled MPC have quite satisfying performances.The presented results indicate that,amongst them,GRNN appears to provide the best performance.
