Wavelet networks in online modeling of circulating fluidized bed

Circulating fluidized bed (CFB) is a technology used in the design of clean coal power plants. CFB has applications in fuel and petroleum industries for processes. One of the major problems in the study and design of these large, complex systems is modeling and predicting of their characteristic behavior. The objective of this paper is to present the result of an attempt to build an online model for CFB using wavelet networks. Wavelet theory and neural networks are combined into a single method called wavelet networks to overcome the difficulties in the design of adaptive control system for nonlinear plants. No prior offline training phase and no explicit knowledge of the structure of the plant are required. Construction of a wavelet network as an alternative to a neural network to approximate the highly nonlinear system CFB is specified and the simulation results are presented.