Removing Time-Scale Separation in Feedback-Based Optimization via Estimators

Abstract

Feedback-based optimization (FBO) provides a simple control framework for regulating a stable dynamical system to the solution of a constrained optimization problem in the presence of exogenous disturbances, and does so without full knowledge of the plant dynamics. However, closed-loop stability requires the controller to operate on a sufficiently slower timescale than the plant, significantly constraining achievable closed-loop performance. Motivated by this trade-off, we propose an estimator-based modification of FBO which leverages dynamic plant model information to eliminate the time-scale separation requirement of traditional FBO. Under this design, the convergence rate of the closed-loop system is limited only by the dominant eigenvalue of the open-loop system. We extend the approach to the case of design based on only an approximate plant model when the original system is singularly perturbed. The results are illustrated via an application to fast power system frequency control using inverter-based resources.