2020 L4DC L4DC 2020

Direct Data-Driven Control with Embedded Anti-Windup Compensation

Abstract

Input saturation is an ubiquitous nonlinearity in control systems and arises from the fact that all actuators are subject to a maximum power, thereby resulting in a hard limitation on the allowable magnitude of the input effort. In the scientific literature, anti-windup augmentation has been proposed to recover the desired linear closed-loop dynamics during transients, but the effectiveness of such a compensation is strongly linked to the accuracy of the mathematical model of the plant. In this work, it is shown that a feedback controller with embedded anti-windup compensator can be directly identified from data, by suitably extending the existing data-driven design theory. The effectiveness of the resulting method is illustrated on a benchmark simulation example.

🚀 Conference Pioneer — L4DC 2020
🌉 Interdisciplinary Bridge — Computer Science and Robotics
🧭 Keyword Pioneer — input saturation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Machine Learning, Mathematics & Optimization, Reinforcement Learning, Robotics