Radial basis functions neural network of vary learning rate based stochastic U-model

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 Neu...

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Bibliographic Details
Published in2011 International Conference on Electrical and Control Engineering pp. 278 - 281
Main Authors WenChao Chang, Weijun Wang, HuiRan Jia
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2011
Subjects
Adaptation models
Aerodynamics
Heuristic algorithms
Mathematical model
Nonlinear dynamical systems
Nonlinear stochastic dynamic systems
On-line estimation
Stochastic processes
Time varying parameters
U-model
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Summary: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).
ISBN:9781424481620
1424481627
DOI:10.1109/ICECENG.2011.6057513