Vehicle Lateral Motion Modeling Using Data-Driven Method

초록

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 the 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 the model derivation process and has similarities to the system. DMD can be used for complicated dynamic systems 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 to 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 validated models. © 2023 IEEE.

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