Title :
Radial basis functions neural network of vary learning rate based stochastic U-model
Author :
Chang, WenChao ; Wang, Weijun ; Jia, HuiRan
Author_Institution :
Hebei Univ. of Sci. & Technol., ShiJiaZhang, China
Abstract :
In this paper, an adaptive tracking control algorithm and its step by step implementation procedure are developed for a class of nonlinear plants within a U-model framework with unknown parameters. A new technique is proposed to design an online control algorithm using the Radial Basis Functions Neural Network (RBFNN).
Keywords :
radial basis function networks; stochastic processes; RBFNN; adaptive tracking control algorithm; learning rate; online control algorithm; radial basis functions neural network; stochastic U-model; Adaptation models; Aerodynamics; Heuristic algorithms; Mathematical model; Nonlinear dynamical systems; Stochastic processes; Nonlinear stochastic dynamic systems; On-line estimation; Time varying parameters; U-model;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
DOI :
10.1109/ICECENG.2011.6057513
