| 1 |
Deep learning based system identification of industrial integrated grinding circuits
Miriyala SS, Mitra K
Powder Technology, 360, 921, 2020 |
| 2 |
A plant-scale validated MATLAB-based fuzzy expert system to control SAG mill circuits
Hadizadeh M, Farzanegan A, Noaparast M
Journal of Process Control, 70, 1, 2018 |
| 3 |
Simulation and optimization of a two-stage ball mill grinding circuit of molybdenum ore
Kwon J, Jeong J, Cho H
Advanced Powder Technology, 27(4), 1073, 2016 |
| 4 |
Survey on higher-level advanced control for grinding circuits operation
Zhou P, Lu SW, Yuan M, Chai TY
Powder Technology, 288, 324, 2016 |
| 5 |
Optimum choice of the make-up ball sizes for maximum throughput in tumbling ball mills
Cho H, Kwon J, Kim K, Mun M
Powder Technology, 246, 625, 2013 |
| 6 |
Disturbance rejection of ball mill grinding circuits using DOB and MPC
Yang J, Li SH, Chen XS, Li Q
Powder Technology, 198(2), 219, 2010 |
| 7 |
Disturbance observer based multi-variable control of ball mill grinding circuits
Chen XS, Yang J, Li SH, Li Q
Journal of Process Control, 19(7), 1205, 2009 |
| 8 |
Application of model predictive control in ball mill grinding circuit
Chen XS, Zhai JY, Li SH, Li Q
Minerals Engineering, 20(11), 1099, 2007 |
| 9 |
Constrained real-time optimization of a grinding circuit using steady-state linear programming supervisory control
Lestage R, Pomerleau A, Hodouin D
Powder Technology, 124(3), 254, 2002 |
