Fixed-Time Prescribed Performance Path-Following Control for Autonomous Vehicle With Complete Unknown Parameters

This article investigates the issue of fixed-time path-following control for autonomous ground vehicles (AGVs) with completely unknown parameters subject to preset error constraints. Before converging the path-following errors, a fixed-time prescribed performance control (PPC) protocol is developed to guarantee the selected nonsingular sliding manifold evolving within the preset boundaries. Then, the fixed-time PPC target for the preview error of the AGV can be achieved by satisfying the parameter inequality. Furthermore, the designed adaptive laws can ensure the control accuracy without knowledge of vehicle parameters. Finally, the hardware-in-the-loop tests of multiple maneuvering conditions demonstrate that the proposed fixed-time PPC protocol can provide superior comprehensive path-following performance for the AGV over the conventional fixed-time controller, and the preview error can never violate the prescribed performance constraints.

Automated summary

This article investigates the fixed-time path-following control problem for autonomous ground vehicles (AGVs) with completely unknown parameters and preset error constraints. A fixed-time prescribed performance control (PPC) protocol is proposed to ensure the evolution of the selected nonsingular sliding manifold within the preset boundaries before converging the path-following errors. By satisfying the parameter inequality, the fixed-time PPC target for the preview error of the AGV can be achieved. Furthermore, the designed adaptive laws guarantee control accuracy without knowledge of vehicle parameters. Hardware-in-the-loop tests demonstrate the superior comprehensive path-following performance of the proposed fixed-time PPC protocol for the AGV compared to the conventional fixed-time controller, with no violation of the prescribed performance constraints on the preview error.