Neural Networks in Feedback Control Systemsadaptive learning controllersapproximate dynamic programming (ADP)dynamic gamesfeedback control systemsneural network feedback control structuresneural networks (NNs)nonlinear systemsdoi:10.1002/9781118985960.meh223K. G. VamvoudakisF.L. LewisShuzhi Sam Ge...
Adaptive system theory controllersNeural netsSummary: The purpose of this paper is to propose an adaptive output feedback controller using wavelet neural networks with nonlinear parameterization for unknown nonlinear systems with only system output measurement. An error observer is used to estimate the ...
The author presents a learning algorithm and capabilities of perceptron-like neural networks whose outputs and inputs are directly connected to plants just like ordinary feedback controllers. This simple configuration includes the difficulty of teaching the network. In addition, it is preferable to let...
By introducing a novel adaptive control architecture, decentralized controllers are developed, which allow for parameter uncertainties and unknown external ... H Min,S Wang,F Sun,... - 《Systems & Control Letters》 被引量: 134发表: 2012年 Prescribed performance adaptive fuzzy output-feedback dynam...
The performance of the NN approach is evaluated through co-simulations of the scheduler, controllers and process dynamics.doi:10.1007/11552451_26Feng XiaZhejiang UniversityYouxian SunZhejiang UniversitySpringer, Berlin, HeidelbergFeng Xia, Youxian Sun, "Neural Network Based Feedback Scheduling of ...
Neural network based adaptive output feedback control: Applications and improvements. Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experime... AT Kutay - Georgia Institute of Technology. 被引量: 0发表...
Feedback linearizationneurocontrollersnonaffine systemsA neural control synthesis method is considered for a class of nonaffine uncertain single-input-single-... Yang, B.-Y,AJ Calise - 《IEEE Transactions on Neural Networks》 被引量: 110发表: 2007年 A neural approach for control of nonlinear syst...
such controllers provide an important bridge to link limb mechanics, motor behaviour and the neural basis of motor control.As a theory, optimal feedback control generates a number of neurophysiological questions on how such a controller is created by the highly distributed circuitry involved in sensor...
Different from the conventional controllers, we propose two classes of novel switching state-feedback controllers which include discontinuous factor sign (.). By doing so, the synchronization error of CGNNs can be controlled to converge zero in a finite time. Moreover, we also...
Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe...