LAPSE:2020.0378
Published Article
LAPSE:2020.0378
Optimal Speed Control for a Semi-Autogenous Mill Based on Discrete Element Method
Xiaoli Wang, Jie Yi, Ziyu Zhou, Chunhua Yang
April 14, 2020
The rotation speed of a mill is an important factor related to its operation and grinding efficiency. Analysis and regulation of the optimal speed under different working conditions can effectively reduce energy loss, improve productivity, and extend the service life of the equipment. However, the relationship between the optimal speed and different operating parameters has not received much attention. In this study, the relationship between the optimal speed and particle size and number was investigated using discrete element method (DEM). An improved exponential approaching law sliding mode control method is proposed to track the optimal speed of the mill. Firstly, a simulation was carried out to investigate the relationship between the optimal speed and different operating parameters under cross-over testing. The model of the relationships between the optimal rotation speed and the size and number of particles was established based on the response surface method. An improved sliding mode control using exponential approaching law is proposed to track the optimal speed, and simulation results show it can improve the stability and speed of sliding mode control near the sliding surface.
Keywords
discrete element method (DEM), optimal speed, SAG mill, sliding mode control
Suggested Citation
Wang X, Yi J, Zhou Z, Yang C. Optimal Speed Control for a Semi-Autogenous Mill Based on Discrete Element Method. (2020). LAPSE:2020.0378
Author Affiliations
Wang X: School of Automation, Central South University, Changsha 410083, China
Yi J: School of Automation, Central South University, Changsha 410083, China
Zhou Z: School of Automation, Central South University, Changsha 410083, China
Yang C: School of Automation, Central South University, Changsha 410083, China
Journal Name
Processes
Volume
8
Issue
2
Article Number
E233
Year
2020
Publication Date
2020-02-18
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8020233, Publication Type: Journal Article
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LAPSE:2020.0378
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doi:10.3390/pr8020233
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Apr 14, 2020
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CC BY 4.0
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Apr 14, 2020
 
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Original Submitter
Calvin Tsay
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