Price-Driven Coordination for Solving Plant-Wide MPC Problems

Two-level model predictive control (MPC) is the dominant multi-variable control technology in current industrial applications. In large-scale MPC applications, such as plant-wide control, two common approaches are centralized and decentralized MPC schemes, which represent the two extremes in the "trade-off" among the desired characteristics of an implemented MPC system. Alternatively the coordination of decentralized MPC systems may offer the best attributes of each of the trade-off extremes. One such coordination scheme is the price-driven method. The price-driven coordination method requires the existence of "equilibrium prices" and has extensive large-scale applications in economic planning. On-line solutions to large-scale optimization problems require an efficient price-adjustment method. As the coordination problem for decentralized MPC falls into the category of limited resource case, this work develops an efficient price-searching algorithm by using Newton's method, in which sensitivity analysis and active set change identification techniques are employed. The proposed price-adjustment strategy is incorporated into a coordinated, decentralized MPC scheme that shows a high degree of accuracy, while retaining the reliability of original decentralized scheme at a reasonable computational load.