RBF Control Research Based on Fuzzy Neural Model

Author

Zheng, Changlu ; Fan, Jian ; Fei, Minrui ; Gao, ZhiNian

Author_Institution

Shanghai Key Lab. of Power Station Autom. Technol., Shanghai Univ., Shanghai, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

3

Abstract

RBF controller based on fuzzy neural network model is given in this paper, which applies field data to model the control object, and then uses the model to adjust the parameters of gauss basis function in RBF controller, such as the central value, the width, and the weights from hidden layer to output layer. In addition, the controller is applied to control the bed temperature of CFB boilers. By comparison with the traditional PED controllers, the simulation result shows that the given controller has shorter response time and better tracking performance.

Keywords

Gaussian processes; fuzzy control; fuzzy neural nets; neurocontrollers; radial basis function networks; CFB boilers bed temperature; PID controller; RBF control research; fuzzy neural model; gauss basis function; Automatic control; Centralized control; Control system synthesis; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Neurons; Temperature control; Three-term control;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5363752

Filename

5363752