Comparing economic model predictive control to basic and advanced regulatory control on a simulated high-pressure grinding rolls, ball mill, and flotation circuit. (February 2023) - Thivierge, Alex; Bouchard, Jocelyn; Desbiens, André
Abstract: Mineral processing plants remain nowadays infamous for their low energy efficiency. Economic model predictive control (EMPC), by directly considering the energy costs, could possibly help reduce their footprint, but its environmental benefits are yet to be clearly quantified. In an attempt to cast some light on this topic, this paper compares the response to a given ore feed size and hardness disturbance sequence of an EMPC to that of basic and advanced regulatory control systems using the profits and the specific energy (power draw/ore feed rate) as metrics. The simulated circuit comprises a high-pressure grinding rolls (HPGR), a ball mill, and a flotation circuit. It is based on population balance modeling and is an extension of previous works. The basic regulatory control (BRC) system comprises only single-input–single-output control loops with proportional–integral (PI) controllers and operates at a fixed feed rate. The advanced regulatory control (ARC) system consists of PI controllers maximizing the plant feed rate with override constraint handling. The results show that (1) ARC generates more revenue and maintains a lower circuit specific energy consumption than BRC, (2) ARC can produce the same economic performance as EMPC because the constraints of the system define the economic optimum, and (3) EMPC can trade revenues for a lower circuit specific energy with a hybrid criterion that penalizes power draw. Highlights: The work compares different control systems on an HPGR grinding circuit. A decentralized PI control system can generate equivalent revenues to an EMPC. EMPC can trade revenues for a lower circuit specific energy.