The control objective of the forced-circulation evaporation process of alumina production is not only to avoid large fluctuations of the level, but also to ensure the product density to track its setpoint quickly. Due...The control objective of the forced-circulation evaporation process of alumina production is not only to avoid large fluctuations of the level, but also to ensure the product density to track its setpoint quickly. Due to the existence of strong coupling between the level loop and the product density loop, and high nonlinearities in the process, the conventional control strategy cannot achieve satisfactory control performance, and thus the production demand cannot be met. In this paper, an intelligent decoupling PID controller including conventional PID controllers, a decoupling compensator and a neural feedforward compensator is proposed. The parameters of such controller are determined by generalized predictive control law. Real-time experiment results show that the proposed method can decouple the loops effectively and thus improve the evaporation efficiency.展开更多
基金Supported by the National Natural Science Foundation of China(61473063)the National Key Technology R&D Program(2012BAJ26B01)+2 种基金the China Postdoctoral Science Foundation(2014M552040,2014M561250,2015M571328)the Special Fund for Agroscientific Research in the Public Interest(201503136)the Key Scientific and Technological Project of Liaoning Province(201500834)
文摘The control objective of the forced-circulation evaporation process of alumina production is not only to avoid large fluctuations of the level, but also to ensure the product density to track its setpoint quickly. Due to the existence of strong coupling between the level loop and the product density loop, and high nonlinearities in the process, the conventional control strategy cannot achieve satisfactory control performance, and thus the production demand cannot be met. In this paper, an intelligent decoupling PID controller including conventional PID controllers, a decoupling compensator and a neural feedforward compensator is proposed. The parameters of such controller are determined by generalized predictive control law. Real-time experiment results show that the proposed method can decouple the loops effectively and thus improve the evaporation efficiency.
