Precise articulation angle tracking for snake-inspired articulated vehicles: An SMC approach with adaptive tracking differentiator

Abstract

This paper tackles the critical challenge of articulation angle control for articulated low-speed heavy-duty vehicles (ALSHDVs), whose tracking accuracy is severely compromised by strong nonlinearities and unmodeled dynamics, such as nonlinear friction, within the hydraulic steering system. To fundamentally enhance steering agility and overcome the limitations of conventional control methods, this paper is inspired by the adaptive undulatory motion of snakes. A novel two-stage control strategy is proposed: firstly, a bio-inspired, smooth sinusoidal trajectory is generated and mapped to a desired articulation angle command, establishing a continuous reference that mimics serpentine locomotion. Secondly, to achieve high-precision tracking of this complex command, a robust controller is architected. The core of this controller is a Sliding Mode Controller (SMC) that governs the hydraulic cylinder. To empower the SMC, an Adaptive Tracking Differentiator (ATD) is integrated as an intelligent signal conditioning unit, which employs real-time adaptive filtering to supply it with robust and noise-resistant estimates of the required higher-order state derivatives. The superiority of the proposed ATD-SMC framework is rigorously validated through co-simulation and hardware-in-the-loop experiments. The results demonstrate that compared to backstepping control, the average absolute tracking error is reduced by over 20%, confirming the effectiveness and practical advantages of this strategy.