Safe data-driven reference tracking with prescribed performance

TL;DR

This paper presents a novel control approach combining a sampled-data zero-order hold controller with a data-driven MPC scheme to achieve prescribed performance in output reference tracking for unknown systems with discrete measurements.

Contribution

It introduces a new two-component control method that integrates data-driven MPC with existing sampled-data control to improve tracking accuracy and control signals.

Findings

Achieves tracking within predefined error bounds.

Significantly improves control signals through data-driven modeling.

Demonstrates effectiveness via numerical example.

Abstract

We study output reference tracking for unknown continuous-time systems with arbitrary relative degree. The control objective is to keep the tracking error within predefined time-varying bounds while measurement data is only available at discrete sampling times. To achieve the control objective, we propose a two-component controller. One part is a recently developed sampled-data zero-order hold controller, which achieves reference tracking within prescribed error bounds. To further improve the control signal, we explore the system dynamics via input-output data, and include as the second component a data-driven MPC scheme based on Willems et al.'s fundamental lemma. This combination yields significantly improved input signals as illustrated by a numerical example.