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

DOI

10.2991/meici-16.2016.66How to use a DOI?

Keywords

Ball mill; Particle swarm optimization (PSO); Neural network; PID control; Constant power

Abstract

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.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li Ai
AU  - Yan Xiong
PY  - 2016/09
DA  - 2016/09
TI  - Ball Mill Automatic Control System Design Based on Particle Swarm Optimization Algorithm
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 320
EP  - 323
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.66
DO  - 10.2991/meici-16.2016.66
ID  - Ai2016/09
ER  -