Optimal control for continuous bauxite grinding process in ball-mill
铝土矿连续磨矿过程球磨机优化控制

Considering the reduction of power consumption of ball-mill, we propose a multi-objective multi-model predictive control for the continuous grinding process of bauxite with bauxite ores coming from different mine sources and with different qualities. In this method, we first build the state-space concentration-predictive model and the finenessprediction model based on the weighted multi-model of size-mass balance; and then, we develop an optimal multi-model predictive control scheme for optimizing multiple objectives including the interval control of concentration and fineness of the discharged ore pulp from the ball-mill, along with economic indices. The local optimal control law of the controller is obtained by minimizing a multiplier penalty function. The simulation and the field test results show the effectiveness of this method.