【摘要】 为了解决传统的重介质分选过程忽略悬浮液黏度的建模与控制问题，首先分析了重介质分选工艺流程，以控制磁性物含量的方式控制黏度。然后建立了以补水阀和分流阀为控制量，悬浮液密度和磁性物含量为被控量的双输入、双输出控制模型。最后设计出基于模型预测控制(MPC)的悬浮液密度和黏度控制器。仿真结果表明：与传统的PID和前馈解耦控制器相比，MPC算法的超调量更小、抗干扰能力和鲁棒性更强。更多还原

【Abstract】 In order to solve the problem of modelling and controlling the suspension viscosity neglected by the traditional dense medium separation process, the dense medium separation process was first analyzed to control the viscosity by controlling the magnetic content. Then a dual-input, dual-output control model was established with the make-up valve and diverter valve as the control quantities, and the suspension density and magnetic content as the controlled quantities. Finally, a suspension density and viscosity controller based on model predictive control(MPC) is designed. Simulation results show that the MPC algorithm has smaller overshoot, better interference immunity and robustness than traditional PID and feed-forward decoupling controllers.更多还原