Abstract:

An improved BP neural network PID control algorithm is proposed to optimize and compensate the PM2.5 measuring system for a better accuracy.Firstly,the velocity formula of particle swarm optimization algorithm is improved,then the improved PSO algorithm is applied to optimize the BP neural network to adjust the PID parameters online,and finally the improved PSO optimize BP neural network PID control algorithm and the traditional PID are simulated.The result proves that the improved PSO optimize BP neural network PID control algorithm can improve the accuracy of measurement with a reduced error compared with PID.

Key words: PSO;BP neural network;PID control;accuracy of measurement