DocumentCode :
2303184
Title :
Research on RBF tuning PID and fuzzy immune control system of superheat temperature
Author :
Xue, Yang ; Yan, ZhenJie
Author_Institution :
Fac. of Electr. & Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
Volume :
7
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
3528
Lastpage :
3531
Abstract :
The main steam temperature control system is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant, which has the characteristics of large inertia, long time-delay and time-varying, etc. Thus conventional PID control strategy cannot achieve good control performance. Prompted by the feedback regulation mechanism of biology immune response and neural network, a composite control strategy based on RBF tuning PID and fuzzy immune control is presented in this paper. It has stronger robustness and better self-adaptive ability, which can be adaptive to the change in the parameters of the controlled plant. A simulation study of the main steam temperature control system shows that this control strategy is effective, practicable and superior to conventional PID control.
Keywords :
adaptive control; fuzzy control; robust control; self-adjusting systems; steam plants; temperature control; three-term control; RBF tuning PID control system; fuzzy immune control system; power plant; robustness; self-adaptive ability; steam temperature control system; superheat temperature; Artificial neural networks; Immune system; Power generation; Radial basis function networks; Temperature control; Tuning; RBF neural network; fuzzy control; immune control; superheat temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5584089
Filename :
5584089
Link To Document :
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