Abstract
The main steam temperature in a power plant is a typical process with nonlinear, dead time, time-varying parameters. Different methods have been employed to control this process, among which one may refer to conventional Internal Mode Control (IMC). In this paper a new neural network-based adaptive IMC-PID controller is proposed. Two neural networks (NN) are employed to identify the plant’s model and to tune the parameters of the IMC-PID controller. The parameters of IMC-PID controller are calculated by a neural network, while another neural network is used to identify the plant. The weights of both neural networks are adjusted on-line and this will compensate the characteristics variation and uncertain non-linearity of the process. To show the performance of the proposed method, it is applied to a steam power plant. The simulations results show the effectiveness of the proposed strategy.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Yu, K.J., Lv, J.H.: The Optimization Control of Main Steam’s and First Stage Steam’s Temperature in the Boiler. Power Engineering 24, 212–217 (2004)
Zeng, J., Xie, Y.C., Chen, L.: Design of Main Steam Temperature Cascade Control System Based on Fuzzy Self-Tuning PID Controller. IEEE International Conference on Intelligent Computation Technology and Automation (ICICTA) 1, 878–881 (2008)
Yang, X.Y., Liu, X.P., Xu, D.P.: AFSMC-PID Control for Main Steam Temperature. In: IEEE International Conference on Machine Learning and Cybernetics, vol. 4, pp. 1872–1876 (2008)
Vu Luan, T.N., Lee, J., Lee, M.: Design of Multi-loop PID Controllers Based on the Generalized IMC-PID Method with Mp Criterion. International Journal of Control, Automation, and Systems 5, 212–217 (2007)
Shen, X.Z., Yue, Y.J., Feng, D.Q.: Application of Internal Model Control to the Process of Printing and Dyeing. Journal of Zhengzhou Institute of Light Industry 18, 3–5 (2003)
Lee, Y., Lee, M., Park, S., Brosilow, C.: PID Controller Tuning for Desired Closed Loop Responses for SISO Systems. AIChE Journal 44, 106–115 (1998)
Narendra, K.S., Balakrishnan, J.: Adaptive Control Using Multiple Models. IEEE Transaction Automatic Control 42, 171–187 (1997)
Jin, X.Z., Wei, G.Y., Yang, Y.Q.: Multi-IMC Adaptive Control System for Main Steam Temperature in the Power Plant. In: Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, pp. 676–681 (2005)
Yazdizadeh, K.K.: Identification of a Turbogenerator Using Adaptive Time Delay Neural Networks. In: The IEEE Conference on Control Applications, pp. 1–4 (1998)
Yazdizadeh, K.K.: Adaptive Time Delay Neural Network Structures for Nonlinear System Identification. Journal Neurocomputing 47, 1–34 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Abbaszadeh Naseri, M., Yazdizadeh, A. (2009). Neural Network-Based IMC-PID Controller Design for Main Steam Temperature of a Power Plant. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_120
Download citation
DOI: https://doi.org/10.1007/978-3-642-01510-6_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01509-0
Online ISBN: 978-3-642-01510-6
eBook Packages: Computer ScienceComputer Science (R0)