Application of neural network model reference adaptive control in coal-fired boiler combustion system

This paper proposes a neural network model reference adaptive PID control method based on RBF neural network identification. This approach can identify the controlled plant on-line with the RBF neural network identifier (NNI), and the weights of the adaptive PID controller (NNC) are adjusted timely...

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Published inProceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826) Vol. 1; pp. 564 - 567 vol.1
Main Authors Jian-Qiang Li, Ji-Zhen Liu, Yu-Guang Niu, Cheng-Lin Niu, Wei Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2004
Subjects
Adaptive control
Adaptive systems
Boilers
Combustion
Control systems
Neural networks
Power generation
Programmable control
Temperature
Three-term control
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Summary:This paper proposes a neural network model reference adaptive PID control method based on RBF neural network identification. This approach can identify the controlled plant on-line with the RBF neural network identifier (NNI), and the weights of the adaptive PID controller (NNC) are adjusted timely based-on the identification of the plant. So the controller is adaptive and the system can be controlled effectively. This approach is also applied to the re-heated temperature plant with long time-delay, large inertia and time-variation in power plant. Research result shows that the controller performs very well when there is disturbance or when plant parameter varies. The robust plant has adaptive abilities that can be easily accomplished on-line.
ISBN:0780384032
9780780384033
DOI:10.1109/ICMLC.2004.1380755