Multi-objective Optimization Control of Filling Concentration in Metal Mines
Slurry concentration has characteristics of hysteresis and time-varying in conventional PID control,which is easily affected by the properties of tailings and particle size.Therefore,a multi-objective optimization control strategy for slurry concentration is proposed.By analyzing the filling process flow,a multi-objective control model for slurry concentration is established according to setting multi-objective decision variables and establishing corresponding objective functions and constraints.The slurry concentration is optimized by underflow concentration,filling quality and filling cost,the model was solved by genetic algorithm and simulated in MATLAB.Through the simulation curve,the multi-objective optimization algorithm meets the control requirements of qualified quality and low cost in terms of evaluation indicators.Compared with the traditional PID control algorithm,the multi-objective optimization control algorithm has faster response speed and stronger robustness.Since the operation of the filling system,the slurry concentration has stabilized at 70％±1％,and the filling cost has decreased by 15％,which meets the requirements of industrial production.
slurry concentrationmulti-objective optimizationgenetic algorithmoptimal control
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