A Model-Based Expert System for Determining Optimal Control Inputs in Purification Process Control

Abstract

One important step in zinc hydrometallurgy is the purification process, which involves removing impurities such as copper, cadmium and cobalt from a zinc sulfate solution to obtain a satisfactory electrolyte. The key point in the control of the purification process is the determination of the optimal amounts of zinc dust, ethylxanthic acid sodium salt and copper sulfate that are added to the reaction tanks. This paper describes a methodology for determining the optimal amounts by using a model-based expert system technique. First, a static mathematical model is established based on the chemical reactions involved and experimental data on the process. Then, it is modified in accordance with the experience and knowledge of ‘expert’ personnel and with data on the process, and a rule model is established. Finally, the modified mathematical model and the rule model are combined into a model-based expert system that determines the optimal amounts. The results of an actual run show that a control system using the proposed methodology provides not only a high-purity product but also significant economic benefits.