Adaptive Event-Triggered Path Tracking Control With Proximate Appointed-Time Prescribed Performance for Autonomous Ground Vehicles

Path tracking control is crucial for autonomous ground vehicles (AGVs), but it faces challenges from model nonlinearity, parameter variations, and external disturbances. This article proposes a novel model-free path tracking controller that achieves appointed-time performance and alleviates the communication burden. Initially, the path tracking model is abstracted as an unknown nonlinear system, bypassing the complexities of time-varying nonlinearity. A proximate appointed-time prescribed performance function (PPF) is then proposed, whose settling time can be preset arbitrarily using a nonpiecewise function with less conservatism. Subsequently, by utilizing an error scaling function to manage the entry capture problem, a dual-level constrained prescribed performance control (PPC) is developed to ensure proximate appointed-time stability of the preview error and its derivative regardless of initial constraints. Furthermore, an adaptive event-triggered mechanism, inspired by the encoder-decoder concept, transmits only two-bit signals aperiodically, substantially decreasing communication bandwidth requirements. Experimental results confirm the effectiveness, robustness, and efficiency of the proposed scheme.