Dynamic Mode Decomposition으로 유도된 차량 동역학 특성 분석

다국어 초록 (Multilingual Abstract)

Designing a control is the process of deriving the system’s dynamic equation and finding a way to stabilize the derive system model. However, the derivation of system model is complicated, and depending on the characteristics of the system, it may be difficult to design the controller. In this paper, we propose a data-driven model derivation method DMD(Dynamic Mode Decomposition) that simplifies model derivation process and has similarity to the system. DMD can be used for complicated dynamic system and has advantages in designing controllers because the derived model is linear. However, in order to take these advantages in the control design, it is first show the similarity between the DMD derived model and the system. Therefore, we used the vehicle dynamics simulation CarSim to derive various models and analyze how to derive validate models.