Abstract
In order to identify the controlled objects which are nonlinear time-delay processes with slow time-varying in the thermal system accurately, the Hammerstein model and particle swarm optimization (PSO) algorithm were used in this paper. For the Hammerstein model discussed in this paper, the polynomial and difference equations were used to express the nonlinear part and linear part of Hammerstein model, respectively. This study used the PSO algorithm to find the optimal solution of Hammerstein model’s undetermined parameters in the parameters space. For illustration, an example of main-steam temperature system identification was utilized to show the feasibility of the Hammerstein model based on PSO algorithm in identifying the thermal system processes. The PSO-based Hammerstein model can effectively represent the controlled objects which are nonlinear time-delay processes in the thermal system and thus a class of identification problems with nonlinearity in thermal system can be solved.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lina H (2009) Main-steam temperature system modeling based on PCA and neural network. North China Electric Power University, Baoding
Narendra KS, Gallman PG (1966) An iterative method for the identification of nonlinear systems using a Hammerstein model. IEEE Transactions on Automatic Control 11(3):546–550
Michelle W (1997) Complex-the science born at the edge of order and chaos. Joint, Beijing
Bo L (2010) Particle swarm optimization and its application. Electronic Industry, Beijing
Tao J (2010) Research on identification of Hammerstein model. Xi’an University of Technology, Xi’an, Shaanxi
Weixing L, Huidi Z, Shirong L et al (2006) The Hammerstein model identification based on PSO. Chin J Sci Instrum 27(1):75–79
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this paper
Cite this paper
Wang, D.F., Ren, Y.Y., Liu, C.L., Han, P. (2014). Identification of Thermal Process Using Hammerstein Model Based on Particle Swarm Optimization Algorithm. In: Xing, S., Chen, S., Wei, Z., Xia, J. (eds) Unifying Electrical Engineering and Electronics Engineering. Lecture Notes in Electrical Engineering, vol 238. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4981-2_214
Download citation
DOI: https://doi.org/10.1007/978-1-4614-4981-2_214
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-4980-5
Online ISBN: 978-1-4614-4981-2
eBook Packages: EngineeringEngineering (R0)