Title :
A stable neural network-based controller for class of nonlinear systems
Author :
Yadmellat, P. ; Samiei, E. ; Talebi, H.A.
Author_Institution :
Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
A novel method to solve the stabilization problem for a class of nonlinear affine single-input systems using neural networks is proposed in this paper. The controller is based on feedback linearization where the control signal is directly estimated by a nonlinear in parameter neural network (NLPNN). A modified Back Propagation (BP) algorithm with e-modification is used to update the weights of the network. The stability of overall closed-loop system is shown using Lyapunov method. To evaluate the performance of the proposed controller, a set of simulations is performed on a Rossler chaotic system.
Keywords :
Lyapunov methods; backpropagation; closed loop systems; neurocontrollers; nonlinear control systems; stability; Lyapunov method; Rossler chaotic system; back propagation algorithm; closed-loop system; feedback linearization; neural network-based controller stability; nonlinear affine single-input systems; parameter neural network; Chaos; Control systems; Linear feedback control systems; Lyapunov method; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems; Performance evaluation; Stability;
Conference_Titel :
Control Applications, (CCA) & Intelligent Control, (ISIC), 2009 IEEE
Conference_Location :
Saint Petersburg
Print_ISBN :
978-1-4244-4601-8
Electronic_ISBN :
978-1-4244-4602-5
DOI :
10.1109/CCA.2009.5281011
