Abstract
Expert and predictive multivariable control algorithms for a conventional copper flotation circuit were assessed through simulations. These simulations were carried out with a nonlinear dynamic model, derived from mass balances and empirical relationships, that qualitatively reproduced the dynamic behaviour of a real plant well. In order to make the simulations more realistic, they included noisy measurements, stochastic parameter variations and input disturbances. New expert algorithms were able to keep the plant operating within a pre-defined zone for long periods without complete control saturation, unlike previous expert controllers. In addition, the inclusion of constraints in a multivariable predictive algorithm verified improved control system regulation and flexibility.
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