Optimization control of hydrometallurgical leaching process based on IDE-MPC

Abstract

• A dynamic model is built for the hydrometallurgical leaching process based on reaction mechanism analysis. • The steady-state economic optimization model of the leaching process is established. • An improved PSO algorithm is proposed to solve the economic optimization problem of the leaching process. • A new control method combining the IDE algorithm and MPC is used to control the leaching process. The utilization rate of raw materials during the hydrometallurgical leaching process has a great influence on the whole economic benefits of the hydrometallurgy plant, so it is necessary for the leaching process to improve the utilization of materials using optimization control methods. In this paper, the dynamic model for the hydrometallurgical leaching process of a gold hydrometallurgy plant is first built based on the reaction mechanism of the process. Then, the model parameters are identified using least-squares fitting. Thereafter, with the maximum economic benefit as the objective function, the steady-state economic optimization model of the leaching process is established, and an improved particle swarm optimization algorithm is used to solve the model. Taking the optimization results as the control objective, a model predictive control method based on an improved differential evolution algorithm is proposed to control the leaching process, so as to improve the intractability and anti-disturbance performance of the controller for the leaching process. The simulation results show that the proposed optimization and control methods achieve satisfactory effects.