| The preparation of methanol from coke oven gas is an important way of methanol production. In the process, the working stability of the methanol synthesis tower is directly related to the quality of the methanol, due to the non-linear, time-varying,time-lag of the tower, week self-adaption,and mathematical model is hard to determine,robustness for traditional PID control method based on PLC,and large volume,high cost, poor compatibility of the PLC. As the tower outlet temperature is a direct reflection of the tower temperature, so use methanol synthesis tower as a controlled object, studying a control system to control the controlled object through the outlet temperature of methanol synthesis gas control tower, in order to obtain high purity methanol.This system use the neural network control algorithm has the advantages of nonlinear, time delay and high uncertainty in dealing with complex system. Combining high performance, low cost and low power consumption of the ARM9, then put forward a kind of control method to synthesis tower temperature with ARM9 and neural network PID control algorithm. In the study process of methanol synthesis temperature control system, then designed the hardware circuit, and three layers BP neural network’s activation function and the weight, and wrote software algorithm. By embedding the control program of neural PID algorithm into the ARM9 chip. Completing real time control and displaying of the control process. Simulations are made to compare with conventional PID control and BP neural network PID control through MATLAB.Meanwhile, under the Lab VIEW platform, the design of the automatic monitoring and control system of the tower, realized the monitoring and control of realtime temperature on Synthesis tower.The results indicated that this designed control system was of good stable and dynamic characteristics,inflexibility,and strong robustness. This control system has a good application prospect in methanol synthesis temperature controlling. |
PDF Full Text Request