Ensuring adaptive safe control performance in the persistence of uncertainties poses great challenges for safety-critical autonomous vehicle control systems. This article investigates the adaptive safety control design for the trajectory tracking problem on a four-wheel-drive electric vehicle (4WDEV) by employing adaptive control barrier functions (CBFs) to formulate the state constraints of the affine control system. Specifically, the tracking-error model is first established with consideration of integrated longitudinal and lateral dynamics of the 4WDEV. Then, adaptive CBFs (ACBFs) and control Lyapunov functions (CLFs) are employed to formulate the safety constraints and stability conditions of the constrained control problem, respectively. Through the safety control design, the trajectory tracking control problem is constructed as quadratic programming (QP). The adaptive performance is enhanced by introducing the time-varying parameters for CBFs to be adjusted by an auxiliary system, which also enhances the feasibility of the quadratic optimization. The effectiveness of the proposed safety control design is verified though simulations of different scenarios and hardware-in-the-loop (HiL) experiments. Through comparisons among the conventional high-order CBFs (HOCBFs) and baseline controllers, for example, linear quadratic regulator (LQR) and model predictive control (MPC), the superiority of the proposed control design in the aspect of safety satisfaction and adaptability is effectively demonstrated.
Safety-Critical Control of 4WDEV Trajectory Tracking via Adaptive Control Barrier Function
IEEE Transactions on Transportation Electrification ; 10 , 4 ; 10361-10373
01.12.2024
2646260 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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