14 papers
Koopman meets input-output data: Data-driven output-feedback control of nonlinear systems with closed-loop guarantees
Robin Strässer, Julian Berberich, Manuel Schaller +2
Data-driven control of nonlinear systems from input-output measurements remains a fundamental challenge, as existing approaches with rigorous closed-loop guarantees predominantly r…
A Koopman Set-Membership Approach for Nonlinear Data-Driven Control with Stability Guarantees
Yifan Xie, Zuxun Xiong, Julian Berberich +2
This paper proposes a data-driven controller design method for unknown nonlinear systems based on a Koopman bilinear realization. Using Koopman operator theory, the nonlinear syste…
Data-Driven Min-Max MPC with Integral Quadratic Constraints
Yifan Xie, Julian Berberich, Frank Allgöwer
Data-driven control of nonlinear systems with rigorous guarantees is a challenging control problem. Integral quadratic constraints (IQCs) provide a powerful framework for modeling…
Adaptive Data-Driven Min-Max MPC for Linear Time-Varying Systems
Yifan Xie, Julian Berberich, Frank Allgöwer
In this paper, we propose an adaptive data-driven min-max model predictive control (MPC) scheme for discrete-time linear time-varying (LTV) systems. We assume that prior knowledge…
An overview of systems-theoretic guarantees in data-driven model predictive control
Julian Berberich, Frank Allgöwer
The development of control methods based on data has seen a surge of interest in recent years. When applying data-driven controllers in real-world applications, providing theoretic…
An overview of Koopman-based control: From error bounds to closed-loop guarantees
Robin Strässer, Karl Worthmann, Igor MeziÄ +3
Controlling nonlinear dynamical systems remains a central challenge in a wide range of applications, particularly when accurate first-principle models are unavailable. Data-driven…