Multi-objective optimization based optimal setting control for industrial double-stream alumina digestion process

Abstract

The operation variables, including feed rate of ore slurry, caustic solution and live steams in the double-stream alumina digestion process, determine the product quality, process costs and the environment pollution. Previously, they were set by the technical workers according to the offline analysis results and an empirical formula, which leads to unstable process indices and high consumption frequently. So, a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives, where the key technical indices are predicted based on the digestion kinetics of diaspore. A multi-objective state transition algorithm (MOSTA) is improved to solve the problem, in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm. Then a rule based strategy is designed to make the final decision from the Pareto frontiers. The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production. Results show that the proposed method can achieve the technical target while reducing the energy consumption.

Keywords

double-stream digestion process / optimal setting control / multi-objective optimization / state transition algorithm / rule based decision making

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