Application of Ant Colony Algorithm in PID Parameter Optimization for Mining Hoist Direct Torque Control System

The mining hoist is a key transport equipment to transfer the workers and coal between the mining well and the ground. In the traditional mining hoist direct torque control system, there are some disadvantages such as torque pulsation in the low speed range, which is very dangerous to safety production. In this paper, a novel control strategy using ant colony algorithm (ACA) to optimize the parameters of the speed PID controller is proposed to overcome the shortcomings, the algorithm based on the direct torque control model is obtained to meet real time control requirement, and the ACA optimization steps are described, the speed PID controller parameters are debugged and optimized using ACA. The theory analysis and simulation results indicate that the torque ripple of the system is observably reduced, and the system speed overshoot is small after the parameters of the speed PID controller are optimized with ACA, so the stability of the mining hoist direct torque control system is improved.