Authors: Jinxing Lin, Jiong Shen
Addresses: School of Energy and Environment, Southeast University, Nanjing 210096, China. ' School of Energy and Environment, Southeast University, Nanjing 210096, China
Abstract: The boiler-turbine unit (BTU) is a highly non-linear, multivariable and time-varying system. The normal linear or quasi-linear modelling cannot reflect the real non-linear characteristics of the BTU, degrading control precision and operating performance. This paper deals with non-linear modelling of a drum-type BTU using an evolving Takagi-Sugeno (T-S) fuzzy model. A novel method based on fuzzy clustering, least-squares and genetic algorithms (GA) is proposed to construct a |parsimonious| dynamic T-S fuzzy model with high generalisation ability. In this method, a self-organising fuzzy model generation strategy based on GA is proposed for selecting the optimal structure (including the number of rules and input variables) and antecedent parameters of the fuzzy model. Furthermore, the modified Akaike information criterion is introduced as the evaluation function of GA, which enables the self-organising strategy to choose an optimal fuzzy model with a good trade-off between fitting the training data and keeping the model simple. The simulation results show that the developed dynamic T-S fuzzy model can accurately approximate the global behaviour of the non-linear physical model with a low number of rules and fewer input variables. Further, based on the obtained T-S fuzzy model, valid control strategy studies such as predictive control can be developed.
Keywords: boiler-turbine unit; BTU; Takagi-Sugeno fuzzy modelling; fuzzy clustering; genetic algorithms; Akaike information criterion; least squares; simulation; predictive control.
International Journal of Modelling, Identification and Control, 2011 Vol.12 No.1/2, pp.56 - 65
Published online: 31 Dec 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article