Expert control strategy using neural networks for electrolytic zinc process

来源期刊：中国有色金属学报(英文版)2000年第4期

论文作者：吴敏 唐朝晖 桂卫华

文章页码：555 - 1064

Key words：electrolytic process; expert control; neural networks; rule models; single-loop control

Abstract: The most important parameters which control the electrolytic process are the concentrations of zinc and sulfuric acid in the electrolyte. An expert control strategy for determining and tracking the optimal concentrations was proposed, which uses neural networks, rule models and a single-loop control scheme. First, the process was described and the strategy that features an expert controller and three single-loop controllers was explained. Next, neural networks and rule models were constructed based on statistical data and empirical knowledge on the process. Then, the expert controller for determining the optimal concentrations was designed through a combination of the neural networks and rule models. The three single-loop controllers used the PI algorithm to track the optimal concentrations. Finally, the implementation of the proposed strategy were presented. The run results show that the strategy provides not only high-purity metallic zinc, but also significant economic benefits.