4 papers · 1 filter
Deep Koopman risk-preview supervised LTV-MPC for direct yaw moment control of distributed drive electric vehicles
Wenjie Wang, Hao Chen, Ran Shu +2
Always-on direct yaw moment control (DYC) improves vehicle stability during critical maneuvers but can introduce unnecessary interventions under low-risk conditions. This paper pro…
Adaptive Deep Koopman Operator for Vehicle Dynamics Modeling: A Physics-Informed and Tire-Force-Driven Approach
Wenjie Wang, Hao Chen, Ran Shu +3
Accurate and adaptive modeling of vehicle dynamics is paramount for the safety of autonomous driving systems, particularly under extreme maneuvers and time-varying parameters. Whil…
Incorporating ESO into Deep Koopman Operator Modelling for Control of Autonomous Vehicles
Hao Chen, Chen Lv
Koopman operator theory is a kind of data-driven modelling approach that accurately captures the nonlinearities of mechatronic systems such as vehicles against physics-based method…
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles
Hao Chen, Xiangkun He, Shuo Cheng +1
Modeling of nonlinear behaviors with physical-based models poses challenges. However, Koopman operator maps the original nonlinear system into an infinite-dimensional linear space…