Research On Synthesis Approach Of Predictive Control In Gas-collector Pressure Of The Coke Oven

Coke is the main raw material in the metallurgical industry for smelling iron. In the coking process, large amount of by-product gas will be generated from coke ovens. It is an important link in the iron and steel production, which not only saves energy but also reduces environmental pollution. The stability of gas-collectors’ pressure directly affects the gas quality, 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 the coke ovens.The gas collecting process of the coke ovens is a highly complex industrial process. Its characteristics of multivariable, strong coupling, nonlinearity, and time-varying 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 the coke ovens in Anshan Iron and Steel Group, this paper has mainly studied the date-driven based modeling method and the synthesis approach of predictive control method used in the gas-collector pressure control which under comprehensive consideration on the physical features and technological characteristics of the gas-collector pressure system for the coke oven.Firstly, by analyzing the physical properties and the process characteristics of the gas-collector pressure system for the coke oven, this paper draws a conclusion that the gas-collector’pressure can be effectively controlled by adjusting the automatic butterfly valve in the gas-collector. For the characteristics of multivariable, strong coupling and nonlinearity in the gas-collector pressure system, according to gas-collectors’ historical data of Anshan Iron and Steel Group and field survey, three typical operating conditions has been divided and the respective state-space model has also been built by use of subspace identification algorithm based on principle component analysis(CSIMPCA). Considering that the time-varying characteristic of the gas-collector, the corresponding perturbation term has been added to each state-space model so as to represent the characteristic. Secondly, on the basis of models expanded in different stable working points, this paper has designed a Luenberger state observer to estimate the state of the gas-collector pressure system according to the process characteristics and control requirements of the site. By use of the estimated state, this paper has adopted the synthesis approach of state estimation based output-tracking MPC algorithm to stabilize the gas-collector at the required settings nearby through comprehensive consideration of each operating condition point and real-time performance requirements.Finally, with the help of MATLAB, this paper has established the simulation model for gas-collector system and its control system, and a simulation for the adopted synthesis approach of output-tracking MPC algorithm as well as a comparison with the traditional PID algorithm have also been carried out. The results of simulation show the effectiveness and Anti-jamming of synthesis approach of predictive control at different operating condition.