Simultaneous Disturbance Model and Controller Estimation for Regulatory Control via VRFT

Abstract

The study considers a direct controller parameter design for regulatory control using one-shot experimental data contaminated with random disturbances. The proposed approach employs an idea of reference model matching, and provides an estimation method for simultaneous disturbance and the desired controller that makes the closed-loop system match with the reference model using a predictive error method (PEM). The study also presents an identifiability condition that assures local uniqueness of the estimated parameters. Finally, a numerical example demonstrates effectiveness of the proposed approach.