Optimization Control of Mineral Processing and Crushing System Based on Neural Network PID

Lian-cheng MA, Yong ZHANG, Qing-yao MENG

Abstract


The crushing feed production process is a key link in the beneficiation industrial process, requiring the crusher to be “packed” to the mine to improve the efficiency of the entire crushing process. This paper proposes a control strategy based on neural network PID algorithm for fine-grained system. Using the neural network algorithm to optimize the parameters of the PID controller. The simulation results show that the optimization control method has strong anti-interference, good robust performance and fast convergence, which can be further applied to the crushing process control system.

Keywords


Feed control, Neural Networks, PID controller


DOI
10.12783/dtcse/aicae2019/31444

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