2007
DOI: 10.1016/j.mineng.2006.08.015
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Optimal control of a rougher flotation process based on dynamic programming

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Cited by 38 publications
(8 citation statements)
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“…The supervisor controller considers an Horizon H = 2 and λ = .1. Previous results, Maldonado et al (2007) have shown that the optimal solutions mainly considered movements in the first three cells. Thus, in this work the optimization problem will only consider the first three setpoints as independent variables.…”
Section: Simulationsmentioning
confidence: 92%
“…The supervisor controller considers an Horizon H = 2 and λ = .1. Previous results, Maldonado et al (2007) have shown that the optimal solutions mainly considered movements in the first three cells. Thus, in this work the optimization problem will only consider the first three setpoints as independent variables.…”
Section: Simulationsmentioning
confidence: 92%
“…The original analysis emphasized rejection of entrained particles in the first cells as the mechanism of grade enhancement [8]. Figure 11 shows the results of two campaigns on a 9-cell rougher flotation line at Los Pelambres Mine, Chile [4]. The line comprises 5 banks in a 1-2-2-2-2 configuration (i.e., 1 single cell followed by 4 pairs of 2 cells).…”
Section: Balanced Decreasing Optimalmentioning
confidence: 99%
“…To exemplify this point, consider a bank of 9 cells and assume that only the froth depth in each cell can be manipulated, then for 10 discrete froth depth values in each cell the number of possible froth depth profiles rises to 10 9 ! Attempts to solve this optimization problem have been proposed [4][5][6] but no industrial applications have been reported. This paper reviews three operational strategies to improve bank performance that have been successfully implemented in several industrial operations: air rate profiling, mass-pull (froth velocity) profiling, and Peak Air Recovery (PAR) air profiling.…”
Section: Introductionmentioning
confidence: 99%
“…Dong [29] studied the event triggered iterative ADP method and applied it to the optimal control of grinding process [30]. Ma [31] et al studied the optimal control of flotation cell by using adaptive dynamic programming method. This method can learn from the operation data of flotation cell and improve the controller iteratively.…”
Section: Introductionmentioning
confidence: 99%