Research On Temperature Modeling And Control Of High-temperature Gas Firing Tunnel Kiln

High-temperature gas firing tunnel kiln is an important part of the production of refractory products, and its control level affects the quality of the material directly. Therefore, the temperature control strategy plays an important part in the tunnel kiln control system. How to design a good temperature control strategy for tunnel kiln which can satisfy the produce requirements, enhance the quality of the product, reduce the energy consumption and reduce the pollution, becomes an urgent problem need to solve.In order to study the temperature control strategy of the tunnel kiln, the temperature model is established at first. Because tunnel kiln is very complicated, it is difficult to establish an accurate mathematical model. According to the characteristics of the tunnel kiln, CARIMA (Controlled Auto-Regressive Integrated Moving Average) model is used to describe the controlled system approximatively in this paper. According to the data from the field, the model order has been identified by solving ratio of the determinant, then the parameters of the model can be recognized by least squares method. Finally, the temperature model is proved to be effective by simulation.Tunnel kiln is a complicated object which has some characteristics such as big inertia, large time delay and nonlinearity. Therefore, in this paper, the idea of GPC (Generalized Predictive Control) is introduced into the tunnel kiln temperature control system. However, the basic GPC algorithm is too complex, and morbid matrix may be produced in the operation process. An improved fast algorithm of GPC is applied in this paper, and the ladder control strategy is integrated into the algorithm above, which can improve the simplicity and security of the algorithm. Finally, the controller is designed based on the temperature model of the tunnel kiln. Simulation results show that, when the model is matched, the dynamic response of the system is fast, overshoot is of small amount and anti-interference ability is strong. However, the control performance deteriorates on the condition of model mismatch.For the model mismatch phenomenon which is mentioned above, using fuzzy inference to compensate the controlled quantity is implanted in this paper, and the generalized predictive controller based on fuzzy compensation of the tunnel kiln is designed. In this control algorithm, the control quantity is the amount of generalized predictive control plus fuzzy compensation. Simulation results show that, in the case of model mismatch, the generalized predictive controller with fuzzy compensation can effectively overcome the negative influence of model mismatch. The system has higher control precision, faster tracking speed, smaller overshoot, stronger anti-interference performance and good control performance, so it can meet the requirements of the tunnel kiln temperature control.