Closed-Loop Koopman Operator Approximation
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Abstract (arXiv)
This paper proposes a method to identify a Koopman model of a feedback-controlled system given a known controller. The Koopman operator allows a nonlinear system to be rewritten as an infinite-dimensional linear system by viewing it in terms of an infinite set of lifting functions. A finite-dimensional approximation of the Koopman operator can be identified from data by choosing a finite subset of lifting functions and solving a regression problem in the lifted space. Existing methods are designed to identify open-loop systems. However, it is impractical or impossible to run experiments on some systems, such as unstable systems, in an open-loop fashion. The proposed method leverages the linearity of the Koopman operator, along with knowledge of the controller and the structure of the closed-loop system, to simultaneously identify the closed-loop and plant systems. The advantages of the proposed closed-loop Koopman operator approximation method are demonstrated in simulation using a Duffing oscillator and experimentally using a rotary inverted pendulum system. An open-source software implementation of the proposed method is publicly available, along with the experimental dataset generated for this paper.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 10 of its 50 references that are in the map. First posted on arXiv 27 Mar 2023.
Builds on
10 of 50 references.
References · 10
- 2021Modern Koopman Theory for Dynamical Systemscited by 269
- 2016Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive controlcited by 134
- 2019Active Learning of Dynamics for Data-Driven Control Using Koopman Operatorscited by 31
- 2019Modeling and Control of Soft Robots Using the Koopman Operator and Model Predictive Controlcited by 22
- 2020Advantages of Bilinear Koopman Realizations for the Modeling and Control of Systems with Unknown Dynamicscited by 18
- 2017Model-Based Control Using Koopman Operatorscited by 14
- 2019LMI Properties and Applications in Systems, Stability, and Control Theorycited by 11
- 2021Koopman Linearization for Data-Driven Batch State Estimation of Control-Affine Systemscited by 3
- 2021Linear Matrix Inequality Approaches to Koopman Operator Approximationcited by 2
- 2021System Norm Regularization Methods for Koopman Operator Approximationcited by 2
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Citing papers per year: 2024: 1.
1 paper.