日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2309.10278

Parameter-Varying Koopman Operator for Nonlinear System Modeling and Control

Parameter-Varying Koopman Operator for Nonlinear System Modeling and Control

シェア:XThreadsFacebookLINEはてブBluesky

著者: Changyu Lee, Kiyong Park, Jinwhan Kim

分類: eess.SY, cs.RO, cs.SY, math.OC

原文アブストラクト

This paper proposes a novel approach for modeling and controlling nonlinear systems with varying parameters. The approach introduces the use of a parameter-varying Koopman operator (PVKO) in a lifted space, which provides an efficient way to understand system behavior and design control algorithms that account for underlying dynamics and changing parameters. The PVKO builds on a conventional Koopman model by incorporating local time-invariant linear systems through interpolation within the lifted space. This paper outlines a procedure for identifying the PVKO and designing a model predictive control using the identified PVKO model. Simulation results demonstrate that the proposed approach improves model accuracy and enables predictions based on future parameter information. The feasibility and stability of the proposed control approach are analyzed, and their effectiveness is demonstrated through simulation.