Road-Adaptive Path Tracking Control: An Event-Triggered Flexible Prescribed Performance Method for Autonomous Ground Vehicles
针对自动驾驶车辆在多变道路和通信带宽限制下的路径跟踪问题，提出一种无需车辆模型和参数辨识的道路自适应控制方案，结合柔性预设性能和事件触发机制，实验验证了其有效性、鲁棒性和效率。
Prescribed performance control (PPC) provides new insights into the path tracking problem for autonomous ground vehicles (AGVs), yet conventional algorithms struggle with fluctuating road conditions and limitations for communication bandwidth. To this end, this article develops a novel road-adaptive path tracking scheme that combines flexible prescribed performance with an event-triggered mechanism, without relying on vehicle model or parameter identification. Initially, the path tracking control is abstracted as an unknown nonlinear system, sidestepping model nonlinearity, parameter variations, and external disturbances. The runnel-shaped boundary with appointed-time prescribed performance functions (PPFs) is then introduced, managing initial constraints and mitigating overshoot simultaneously. Subsequently, the flexible PPC (F-PPC) is designed to ensure proximate appointed-time stability, where the auxiliary system adjusts performance boundaries according to road width. Moreover, an adaptive event-triggered mechanism is integrated to minimize communication frequency and bit rate, requiring only 2-bit data transmission and adjusting the trigger threshold dynamically in response to road curvature. Experimental results validate the effectiveness, robustness, and efficiency of the proposed road-adaptive path tracking scheme.