Abstract
Two-level model predictive control (MPC) is the dominant multi-variable control technology in the process industries. 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 extremes. The price-driven coordination scheme 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-adjustment 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.
Published Version
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