Integration of scheduling and control using internal coupling models

In this paper, we present a novel framework for the integration of scheduling and control of process systems. We introduce internal coupling models (ICMs), defined as (low-order) representations of the closed-loop input-output behaviour of the process under supervisory control. We explore the derivation of ICMs for a specific class of input-output linearizing nonlinear controllers. Then, we formulate the scheduling problem as a mixed-integer dynamic optimization under the constraints imposed by the ICM, aimed at finding the optimal setpoint trajectory for the supervisory controller. We illustrate these concepts with a case study, demonstrating that ICM-based scheduling has comparable performance to other scheduling approaches in the absence of plant- model mismatch, and vastly outperforms them when mismatch is present.