Study On Fuzzy Control On The Base Of CFB

People have paid more and more attentions to the burning technology of Circulated Fluid Boiler (CFB) for its unique advanced characteristic since 1970s. It has increased rapidly in the last 20 years and also become the most prospective burning technology in the history of firepower generating electricity. The boiler burning control system has such characteristics as multi-parameters, nonlinear, time variant and close multi-parameters coupling etc, which are hard for the common PID control methods to get good performance and ideally expected effects. Intelligent technology meets this insufficiency and spreads up quickly.The author emphasizes both need and time in the CFB intelligent control system in the exordium. In this chapter, the current circulated fluid intelligent control is demonstrated briefly. The author points out that the FCB intelligent control is still fragmentary and nonsystematic, so lots researchers need to devote themselves into this field.In chapter 2, based on the investigation of references and the principle of CFB, a approximate temperature mathematic model is established according to both mass and energy equilibrium equations.In chapter 3, the author discusses the theoretic controversy of fuzzy control and gives a substantial answer by using the fuzzy control theory.In chapter 3 and 4,based on the deep introduction of the theory in fuzzy controller, I bring forward a self emendation fuzzy controller to optimize the criteria of fuzzy control by researching on three different types of self emendation fuzzy controller. Generally, when the fuzzy regulation and reasoning method is fixation, they aren't rectified. So, rectifying the parameter of fuzzy control including input parameter Ke , Kec , output parameter Ku and adjusting parameter must be used on evolutionary compute.In this paper, ANFIS model was set up ,whose input signals were gas pressure(P) and bed temperature(T), output signal was the increment of coals, Furthermore, introduced the detail of ethylene factory of engineering project. Setting up the RBF neural networks of the bottom of ethylene column, the fuzzy technology was used to simulate the titer of the bottom of ethylene column, which was also a supplement to real model.