Embedding Constrained Model Predictive Control in a Continuous-Time Dynamic Feedback

TL;DR

This paper presents a continuous-time constrained nonlinear control method embedding model predictive control within a dynamic feedback system, enhanced by an explicit reference governor to improve initial condition handling.

Contribution

It introduces a novel continuous-time control scheme embedding MPC as a dynamic system, ensuring stability and constraint satisfaction with an added reference governor for better initial condition management.

Findings

The embedded MPC scheme is asymptotically stable under certain conditions.

Adding an explicit reference governor expands the feasible initial conditions.

Numerical examples confirm the effectiveness of the proposed control approach.

Abstract

This paper introduces a continuous-time constrained nonlinear control scheme which implements a model predictive control strategy as a continuous-time dynamic system. The approach is based on the idea that the solution of the optimal control problem can be embedded into the internal states of a dynamic control law which runs in parallel to the system. Using input to state stability arguments, it is shown that if the controller dynamics are sufficiently fast with respect to the plant dynamics, the interconnection between the two systems is asymptotically stable. Additionally, it is shown that, by augmenting the proposed scheme with an add-on unit known as an Explicit Reference Governor, it is possible to drastically increase the set of initial conditions that can be steered to the desired reference without violating the constraints. Numerical examples demonstrate the effectiveness of the proposed scheme.