Coal Belt Conveyor PID Controller Parameter Regulation with Neural Network

Abstract

The coal belt conveyor is an important transport equipment to transfer the coal between the mining working space and the ground. In the traditional belt conveyor control system, there are some disadvantages such as movement quiver with switch relay controller. In this paper, a control strategy using neural network theory to optimize the parameters of the speed PID controller is proposed to overcome the shortcomings, the direct torque control model is adopted to meet real time control requirement, and the optimization steps are described. The theory analysis and simulation results indicate that the system speed overshoot is small after the parameters of the speed PID controller are optimized with neural network theory, so the stability of the coal belt conveyor electrical control driving system is improved.