The Design Of Tunnel Kiln Control System And Research On Its Temperature Control

The tunnel kiln is an important equipment which is used for burning refractory materials, and the control level of the temperature has the direct effect on the quality of products. So, how to design control system and 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 a question which is need to be solved imminency.The paper takes the practical project as the background, at first, according to the requirement of the produce process of tunnel kiln and detailed analysis of the demand and the characteristic of tunnel kiln, we design control system for tunnel kiln which contain loop control, process supervising and management information system. We use the PLC of Simense to take the loop control of the system and use the configuration software of WinCC to carry out the supervisory function of the system.We need to establish the tunnel kiln temperature model before researching the advanced control strategy. Because the tunnel kiln is a complicated object which is hard to establish an exact mathematic model, so this paper identifies the dynamic model of the tunnel kiln temperature object through BP neural network based on the data from field. After making the matlab simulative experiment, we get the conclusion that the effect of the tunnel kiln temperature model identified by BP neural network is good.The tunnel kiln is a complicated object which has some characteristics, such as, hysteretic property, time-varying and non-linear, these charactertisics causing as to its temperature control more difficult. The conventional PID control technique can't get the perfect control effect because the three parameters of PID can't be set easily, the anti-interference and adapting ability of PID are week, and it depends on the operators' experience. In this paper, we take the tunnel kiln temperature model identified by neural network as an object to be controlled. According to the requirement of the temperature control, we design a kind of new controller based on fuzzy neural network. The controller has a distinct network structure. The learning ability of the neural network is used to revise the parameters of neural to enhance the learning ability of the fuzzy control. At last, making the matlab simulative experiment, we can make the conclusion that kiln temperature control system based on fuzzy neural network has better performance than the kiln temperature control system based on PID in the following aspects:better following performance for temperature varying, less adjusting time, greater anti-interference ability and greater robustness, so, the fuzzy neural network controller can meet the requirements of tunnel kiln temperature control.