Supervisory control of flotation columns using multi-objective optimization |
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Authors: | Oscar Daniel Chuk,Benjamí n R. Kuchen |
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Affiliation: | aInstituto de Investigaciones Mineras, Universidad Nacional de San Juan, Av. Libertador San Mart?´n, No1109 (oeste), J5400ARX San Juan, Argentina;bInstituto de Automática Facultad de Ingenier?´a, Universidad Nacional de San Juan, Av. Libertador San Mart?´n, No1109 (oeste), J5400ARX San Juan, Argentina |
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Abstract: | This work describes a method for supervisory control of flotation columns based on predictive trajectory generation of setpoints to be applied to the local controllers of the process. The system maximizes the profit while keeping quality constraints and engineering indices. It represents an advance over predictive supervisors using a single evaluation function or those that reduce a multi-objective problem to a single-objective one by means a weighted sum. The procedure is founded on multi-objective optimization using non-dominated genetic algorithms, and a new classification criterion of the Pareto optimal set. The system has been tested by simulation against usual perturbations affecting the flotation process and exhibits good performance, provided that the model properly represents the system operation. |
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Keywords: | Column flotation Predictive supervision Multi-objective optimization Process optimization |
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