Research On Model-free Adaptive Decoupling Control Method In Gas-collector Pressure Of Coke Ovens

Coke is the main raw material in the metallurgical industry for iron-smelting. In the coking process, large amount of by-product gas will be generated from coke ovens. Gas gathering process by effectively recycling shortage of gas is an important link in the iron and steel production, which not only saves energy but also reduces environmental pollution. The gas-collector pressure of coke ovens is an important parameter in the coking production, and its stability directly affects the quality of coke and gas, the life-time of ovens as well as the producing environment. Therefore, it is significant for the iron and steel enterprise to study on the control of gas collecting process of coke ovens.The gas collecting process of coke ovens is a very complex industrial process. Its characteristics of multivariable, nonlinearity, strong coupling, and large disturbance are the major difficulties in the control of gas collecting process, so it is hard to achieve effective control when using traditional control methods. Based on the gas collecting process of coke ovens in Anshan Iron and Steel Group, this thesis has mainly studied the mechanism modeling method and the model-free adaptive control method used in the gas-collector pressure control under comprehensive consideration on the physical features and technological characteristics of the gas-collector pressure system for coke ovens.Firstly, this thesis gives the research situation of gas-collector pressure system for coke ovens at home and abroad, and analyzes the physical properties and the process characteristics of the gas-collector pressure system for coke ovens. On this basis, this thesis builds the dynamic mathematical model of the gas-collector pressure system for coke ovens by using the mechanism modeling method, which further explains the characteristics of nonlinearity, coupling, and disturbance in the gas collecting process of coke ovens, and provides simulation model for the verification of follow-up control algorithm.Secondly, this thesis briefly introduces the basic principle of the model-free adaptive control (MFAC). On the basis of it, for the unknown disturbance of coke oven’s gas-collector pressure system and coupling between gas-collector pressures, this thesis adopts RBF neural network to estimate and compensate it. Combined with the MFAC control methods, this thesis designs the model-free adaptive decoupling control algorithm based on the RBF neural network forecast (NN-MFADC), so as to realize the decoupling control of the gas-collector pressure system for coke ovens. In addition, for the problems that mutual restraint parameters affect the performance of the control system and artificial tuning parameters is very difficult in NN-MFADC algorithm, this thesis designs NN-MFADC control scheme based on PSO, and gives the specific parameter optimization steps, so as to further improve the control effect of gas-collector pressure system for coke ovens.Finally, in the MATLAB environment, this thesis has established the simulation model for gas-collector pressure control system, and the control algorithm designed in this thesis has also been verified by simulation. The results of simulation show that NN-MFADC control algorithm can make gas-collector pressures stable within the range of technological requirements, realizes the system’s decoupling, and has certain anti-interference performance, good control effect.