A comprehensive setting method for the optimal setpoint of controlled variables in the zinc smelting solution purification process under multi-variation inlet status

The zinc smelting solution purification process regulates the oxidation-reduction reactions (characterized by the oxidation-reduction potential (ORP)) by controlling the amount of zinc powder added to remove the impurity ions. In order to ensure the optimal operation of the process, the target key technical indicators should be converted into the optimal setpoint of controlled variables (that is, ORP). Based on the mechanism knowledge, fuzzy rules, and preference-guided predictive optimization, a comprehensive setting method for the optimal setpoint of controlled variables under multi-variation inlet status is proposed. It includes a hybrid trend detection method for inlet status, a mechanism model under multiple operating modes, and a fuzzy correction method and a preference-guided predictive optimization method to deal with slight and violent fluctuations in the inlet status, respectively. The experimental results show that the proposed method can obtain the optimal setpoint of controlled variables and reduce zinc powder consumption by approximately 3.6%.