Research On Cfb-fgd System Modeling Based On T-s Fuzzy Model

Circulating fluidized bed for flue gas desulfurization(CFB-FGD) is a novel technology that shows significant advantages in comparison, with other semi-dry FGD technologies. It can also be competitive with the widely-used wet FGD technology in desulfurization efficiency with low calcium sulfur ratio. The advantages of CFB over other technologies include:the production of a dry waste byproduct not requesting sludge handling equipment; no scaling and corrosion problems enabling the use of cheaper materials; smaller space needed and possibility of easily retrofitting existing plants; no requirement of flue gas reheating; flexibility in operation with regard to varying boiler load; low energy consumption; reduced installation and operating costs, and so on, which makes it become the most appropriate FGD technology in China.CFB-FGD is a complex system and establishing its mathematical model is always one of the core problems. Based on "Research and development of the CFB-FGD automation control technology", which is one of the key subjects in "tenth five-year plan", modeling for CFB-FGD system is studied in this paper, in order to further study practical control loops.Firstly, the development situation of FGD technology is introduced systematically. Then the mechanisms and technological processes of the CFB-FGD technology are analyzed. On this basis, three main control loops of the system are deeply researched according to major control parameters in the operating process of CFB-FGD, which are outlet temperature of fume control loop, the emission concentration of sulfur dioxide control loop and the pressure difference of desulfurizing tower control loop. Furthermore, T-S fuzzy models for each control loop are established, including the models of relationships between the water spray quantity and outlet temperature of fume, between desulfurizer feeding coal, circulation ashes feeding coal and the emission concentration of sulfur dioxide, between circulation ashes feeding coal and the pressure difference of desulfurizing tower.Robust competitive cluster algorithm and orthogonal least squares (OLS) method algorithm are used to identify the established T-S models. The advantage of robust competitive cluster algorithm is that the fuzzy rules and initial value of relative parameters need not to be preset and they can be identified only based on the input and output test data of the identified system. At the same time, orthogonal least squares (OLS) method algorithm is proposed to remove redundant or less important clusters during the clustering process in order to extract fuzzy rules that capture the important features of the systems. This kind of model offers a high semantic level, a good generalization capability and high precision.The relationships between inputs and outputs of each loop are verified by the simulation experiment results. And the T-S models are very close approximation to the real system.