Research And Application Of Bp Neural Network Pid Control Algorithm Based On Hybrid Optimization

Air compressor is a kind of equipment for compressing gas.It is widely used in many fields such as national economy and national defense,especially in the food,chemical and pharmaceutical industries.The control of air compressor system is more stringent.However,the air compressor system is a complex high-order,non-linear system,and it is difficult to establish an accurate mathematical model.Generally,the air compressor is controlled by the PID algorithm in the PLC controller.The traditional PID control algorithm is simple.Conventional systems can perform effective control,but for mathematical systems that are difficult to establish,non-linear and changeable air compressor systems,the PID algorithm cannot achieve the ideal control state.Aiming at the defect of PID control,this paper proposes a fuzzy-PID controllerbased air compressor control system by combining a fuzzy algorithm that does not require a mathematical model and can simulate human control strategies.However,the fuzzy rule base in the fuzzy algorithm is too dependent on expert experience.Therefore,this paper proposes to combine the BP neural network with strong self-learning ability and strong nonlinear expression ability with fuzzy algorithm to effectively overcome the above defects.In order to improve the convergence speed of the system,this paper proposes to combine a chicken flock algorithm with a simple structure and high convergence efficiency with a PID algorithm to design an air compressor control system based on a chicken flock-PID controller.In terms of experiments,this paper uses MATLAB software to simulate and analyze the intelligent air compressor control system,and uses the S7-1200 PLC editing module to write the fuzzy neural network-PID algorithm into it,achieving the effectiveness of two different types of air compressors.Control and analyze the energy consumption of the two air compressors before and after the improvement.The research results show that the intelligent air compressor control system based on the flock-PID controller has the fastest response speed,and the intelligent air compressor control system based on the fuzzy neural network-PID controller has the best effect in controlling outlet pressure and energy consumption.lowest.The air compressor system is complex and changeable,and its harsh working environment is not conducive to the timely failure warning and maintenance of the air compressor.Therefore,the research on the remote monitoring technology of the air compressor has been a hot topic in the industry.This paper studies the remote monitoring technology of air compressors.Based on the basic theory of remote monitoring technology of air compressors,the overall structure of remote monitoring of air compressors and the communication network structure are given,and remote monitoring is designed using Lab VIEW.The control interface of the upper computer realizes the real-time monitoring of the air compressor.