Dynamic system modeling of industrial boiler

Industrial processes are commonly nonlinear in nature and include time varying parameters and uncertainties. The basic approach for modeling the system is to use first principle methods e.g. differential equations. One of the major hurdles in developing differential equation model is the complete understanding of the dynamics of the process. The first principle models cannot replicate the true behavior of the system due to many factors. Another approach is based on heuristics. The difficulty behind heuristics based design is that situation arise when unexpected process variables are present and are outside the operator`s experience. These drawbacks motivate us towards model based designing of fuzzy controllers. Section I discusses why we opt for fuzzy controllers in comparison to conventional PID controllers. Section II discusses what techniques have been applied to the available data to identify suitable Regressors. Section III is composed of results acquired from two different modeling and Section IV discusses the results.