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.

With the consideration of actuator faults, including the unknown steering mechanism misalignments and motor traction losses, this article presents a fixed-time control protocol to follow reference paths and velocities for autonomous ground vehicles (AGVs) with preset performance constraints. To provide sufficient large boundaries for the initial states, the hyperbolic tangent function is employed to predefine the constraints with respect to the path-following and velocity control performance. Based on the homeomorphic mapping and barrier Lyapunov theorem, the fixed-time prescribed performance control (PPC) objective-integrated fault-tolerant scheme can be achieved for the controlled AGV. In comparison to three different fixed-time controllers without the fault-tolerant or PPC scheme, the hardware-in-the-loop (HIL) test results demonstrate that the proposed control protocol can always provide superior control performance for the AGV under various maneuvering conditions.

Without knowledge of vehicle model and parameters, a novel complete model-free path-following control strategy is developed for autonomous vehicles based on time-delay estimation (TDE) technique. Different from the existing time-delay control (TDC) approaches, an adaptive nonsingular terminal sliding mode (ANTSM) control law is designed to stabilize the path-following errors without any information of the suitable control gain, which is significant in conventional TDC scheme, and the boundary of the TDE error, which is necessary for sliding-mode-based control scheme. The proposed model-free control structure can dynamically update the gain of the designed controller and the boundaries of the TDE error, and the practical finite-time convergence of the preview error can be achieved. In HIL tests, the comparative results demonstrate the proposed ANTSM model-free control strategy can provide superior comprehensive tracking performance over both the model-based sliding mode controller and the conventional TDC controller while the autonomous vehicle follows desired paths.

This article focuses on the problem of fixed-time path following control for the automated ground vehicles subject to the error constraints and steering dead zone. First, the mean value theorem is employed to extract the input signal embedded in the dead zone function, converting the function into an unknown time-varying control coefficient for the input signal. Then, the Nussbaum-type function is adopted to address this control coefficient in the steering system, eliminating the requirement for prior knowledge of the dead-zone property. By combining with the adaptive law, the path-following performance can be ensured even when the vehicular parameters are unknown. In addition, a fixed-time prescribed performance function is designed to constrain the preview error. Through the homeomorphic mapping transformation technique, the preview error can converge to a small region around the origin within a fixed time. Finally, the experimental studies demonstrate the superior tracking performance of the proposed control scheme.