Hybrid Neural Network Based on ART2—BP Information Fusion Control in Circulating Fluidized Bed Boiler (CFBB)

Abstract

AbstractCirculating Fluidized Bed Boiler (CFBB) involves a kind of combustion boiler that can clean and desulfurize the coal efficiently in the combustion process. It is highly adapted to all kinds of high quality coals and low grade coals. CFB boiler has more superior performance, features and a wide range of applications than other boilers, accordingly, problems on automatic control underlined in the combustion process blocked its wide application. This is a typical thermal object, hard to control,and due to the special combustion type of CFBB that makes it a great inertia, multivariable, strong coupling, nonlinear, time-varying object. This paper designs an ART2-BP-BP Hybrid Neural Network of fusion cluster control system and completes data fusion from the data level, the feature level to the decision level. Results of simulation show that the control system in this paper is feasible and effective, in particular, the control system still has more satisfactory control effects in the case of a variety of sensor failures.KeywordsHybrid neural networkCirculating Fluidized Bed BoilerClustering fusion controlData PreprocessingSituation threat estimate