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For ball mill grinding process random interference by many factors, processes complex mechanism, there was a big inertia and lag, conventional PID control effect was poor, the particle swarm optimization neural network approach was introduced into the mill control system, it had strong robustness, can effectively overcome the mill main motor power nonlinear, time-varying factors such as interference. System was reliable, adjust speed, anti-interference ability, can better achieve constant power automatic control of the ball mill, with good application value.

Ball Mill Automatic Control System Design Based on Particle Swarm Optimization Algorithm