DocumentCode :
424311
Title :
Single-neuron PSD adaptive control based-on Smith predictor for the main steam temperature
Author :
Qin, Zhi-ming ; Zhang, Luan-Ying ; Gu, Jun-jie ; Wang, Lei
Author_Institution :
North China Electr. Power Univ., Baoding, China
Volume :
2
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
1088
Abstract :
The main steam temperature process is regarded as a controllable process with large dead time and immeasurable disturbances. A new single-neuron PSD self-adaptive algorithm that based on Smith predictor was proposed, i.e., a compound controller was combined with Smith predictor and single-neuron PSD self-adaptive controller. Compared with conventional PID controller, the results of simulation show that the system has favorable dynamic properties and good adaptability. The variety of main steam temperature can be maintained in a very small range and it can manipulate variable changes smoothly under large-scale variety of load. Therefore, the scheme has promising application prospects.
Keywords :
adaptive control; neurocontrollers; temperature control; Smith predictor; adaptive control; dead-time system; main steam temperature process; self-adaptive algorithm; single-neuron control; Adaptive control; Artificial neural networks; Control systems; Power generation; Prediction algorithms; Process control; Safety; Temperature control; Three-term control; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1382351
Filename :
1382351
Link To Document :
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