Research Of Imc Algorithm Applied In Ph Value Control System For Flue Gas Resulfurization Of Coal-fired Boiler

The main energy structure of China is based on coal fuels, and coal production and consumption accounts for 75% of the total energy. The sulfur dioxide produced in the combustion of coal is the main sources of the atmosphere pollution in China, in which the most harmful are dust and acid rain. More than 30% of the whole country is under the threat of the acid rain caused by the emission of the sulfur dioxide. A direct result of national economic losses amounts to more than hundred billons. The sulfur dioxide pollution has become the current constraints of China's economic and social sustainable development, so it's imperative to control the pollution.pH neutralization process is a typical nonlinear and long time-delay process. Radial basis function neural network (RBFNN) is a kind of three-layer feed forward neural network with single hidden layer network. RBFNN is a structural simulation of local regularization and mutual overcast in human brain. With local approximation character, it can approximate any continuous nonlinear function with arbitrary precision, and has self-adaptive learning ability to resolve the problems being complex and uncertain. Internal model control (IMC) is a practicable control method, which characteristics are simple structure, less requirement of the model accuracy and easy control, especially has good effects on improving the robustness and ability of anti-disturbance. This paper introduces a method with a combination of RBFNN and IMC to research the pH neutralization process, and discusses a suitable application of wet flue gas desulfurization method.The paper analyzes the characteristics of process, and uses the least-square method to identify the process math model. The paper utilizes the MATLAB to design the controller. Applying RBFNN to internal model control, we can get the positive model and the inverse model through the identification of RBFNN. The internal model control has a better adaptive ability using RBFNN.The system simulation results show that the RBF-IMC structure has better control effects in the pH neutralization process which has nonlinear, great inertial and pure lag characters. These simulations also prove that this structure has good tracking, self-adaptive and robustness ability.