The Research And Design Of Control System For Waste Gas Treatment Based On ARM

As microcomputer's development, the microprocessor with high-speed numerical calculation capacity shows great intelligent level and causes control professionals' interest. Now, many field apparatus adopt embedded system and realize objects' intelligent control. Aiming at the waste gas processing problem in sewage treatment facilities, at the same time, based on combined biological treatment technology using biotrickling filter (BTF) and biological filter (BF), this paper develops and designs the control system for waste gas treatment based on ARM microprocessor.In the process of biological filter waste gas treatment, coupling is obvious between various parameters which also have strong nonlinear characteristics. So it is hard to build its precise mathematic model by mechanism. This paper adopts identification method and simulates the process of waste gas biological treatment by building the object's BP neural network model. Combining with the genetic algorithm optimize the network weights, so that the network training can be avoided of trapping into local minimum points. Use the existing experimental training data and testing data to train and test neural network separately. Simulation results illustrate that the final network model is able to simulate the real object's operation. During waste gas treatment, pH value of circulating water in biological filter is a very important factor and it affects the waste gas's degradation rate. So, neural network predictive control algorithm is presented for pH value control of circulating water in biotrickling filter. The result of the simulation shows that this algorithm has good control effect.The control unit of system adopts Samsung's ARM S3C44B0 (ARM7 kernel) microprocessor. The hardware design includes A/D conversion, system power supply, CAN bus interface, D/A conversion and memory extension circuits. In software design, it transplantsμC/OS-Ⅱas the real-time operating system running on control platform, meanwhile, develops the corresponding driver programs for hardwares and pH value neural network predictive control algorithm program. The remote communication between ARM and host computer in monitoring room is implemented by CAN bus. The application program running in host computer and written by Visual C++ can monitor the serial port data instantly.