Coordination of Distributed Model Predictive Controllers for Constrained Dynamic Processes

Natalia I. Marcos1,  J. Fraser Forbes1,  Martin Guay2
1University of Alberta, Edmonton, AB, Canada, 2Queen´s University, Kingston, ON, Canada


Abstract

In this paper, a coordinated-distributed model predictive control (MPC) scheme is presented for large-scale discrete-time linear process systems. Coordinated-distributed MPC control aims at enhancing the performance of fully decentralized MPC controllers by achieving the plant-wide optimal operations. The 'price-driven' decomposition-coordination method is used to adjust the operations of the individual processing units in order to satisfy an overall plant performance objective. Newton's method, together with a sensitivity analysis technique, are used to efficiently update the price in the price-driven decomposition-coordination method. The efficiency of the proposed control scheme is evaluated using a model of a fluid catalytic cracking process.