COORDINATED DECENTRALIZED MPC FOR PLANT-WIDE CONTROL OF A PULP MILL BENCHMARK PROBLEM

Abstract

In large-scale model predictive control (MPC) applications, such as plant-wide control, the coordination of unit-based MPC controllers has been identified as both an opportunity and a challenge in enhancing the plant-wide control performance. This work discusses an efficient strategy for the coordination of decentralized MPC systems and illustrates the approach with an application to the pulp mill benchmark problem proposed by Castro and Doyle III (2001a). The decentralized unit-based MPC controllers are coordinated at the MPC steady-state target calculation stage by employing decentralized optimization techniques. The off-diagonal element abstraction technique and the price-driven coordination algorithm are used in the development of a coordination mechanism. The pulp mill case study shows that this coordinated, decentralized MPC framework is an effective approach to plant-wide MPC applications, which has high reliability, accuracy and efficiency.