DocumentCode :
1798438
Title :
Multivariable self-tuning PID controller based on wavelet fuzzy neural networks
Author :
Chi-Huang Lu ; Pen-Yu Liao ; Yuan-Hai Charng ; Chi-Ming Liu ; Jheng-Yu Guo
Author_Institution :
Dept. of Electr. Eng., Hsiuping Univ. of Sci. & Technol., Taichung, Taiwan
Volume :
2
fYear :
2014
fDate :
13-16 July 2014
Firstpage :
755
Lastpage :
759
Abstract :
This paper presents a multivariable self-tuning proportional-integral-derivative (PID) controller based on wavelet fuzzy neural networks (WFNNs) for a class of nonlinear systems. A mathematic model using WFNN is constructed for the controlled nonlinear multivariable system, and the self-tuning PID controller is derived via a generalized predictive performance criterion. Numerical simulations exhibit that the proposed multivariable self-tuning PID control law gives satisfactory tracking and disturbance rejection performances.
Keywords :
adaptive control; fuzzy neural nets; multivariable control systems; neurocontrollers; nonlinear control systems; self-adjusting systems; three-term control; WFNNs; disturbance rejection performances; generalized predictive performance criterion; mathematic model; multivariable self-tuning PID controller; multivariable self-tuning proportional-integral-derivative controller; nonlinear multivariable system control; numerical simulations; wavelet fuzzy neural networks; Abstracts; Fuzzy control; Fuzzy neural networks; Numerical models; Radio access networks; Generalized predictive control; Multivariable system; PID controller; Self-tuning; Wavelet fuzzy neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
ISSN :
2160-133X
Print_ISBN :
978-1-4799-4216-9
Type :
conf
DOI :
10.1109/ICMLC.2014.7009704
Filename :
7009704
Link To Document :
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