Predictive functional control for challenging dynamic processes using a simple prestabilization strategy

Abstract

Predictive functional control (PFC) is a straightforward and cheap model-based technique for systematic control of well-damped open-loop processes. Nevertheless, its oversimplified design characteristics are often the cause of diminished efficacy in more challenging applications; processes involving lightly damped and/or unstable dynamics have been particularly difficult to control with PFC. This paper presents a more sustainable solution for such applications by integrating the concept of prestabilization within the predictive functional control formulation. This is essentially a two-stage synthesis wherein the undesirable open-loop dynamics are first compensated, using a well-understood classical approach such as proportional integral derivative (PID), before implementing predictive control in a cascade structure. The proposal, although comes with significant implications for tuning and constraint handling, is, nonetheless, straightforward and provides improved closed-loop control in the presence of external perturbations compared to the standard PFC and the PID algorithms, as demonstrated with two industrial case studies.