• A nonlinear off-road electric vehicle model including terrain and actuator faults is developed • An adaptive super-twisting sliding mode controller is designed for velocity tracking • An extended state observer estimates terrain-induced disturbances in real time • Finite-time stability is proven using Lyapunov-based analysis • Simulations show improved tracking, reduced chattering, and fault tolerance Off-road electric vehicles (OEVs) operate under highly nonlinear dynamics, strong terrain–vehicle interactions, and actuator degradations, which significantly deteriorate speed tracking performance and system reliability. This article proposes an adaptive super-twisting sliding mode control method with an extended state observer (ASTSMC-ESO) for longitudinal speed control of nonlinear OEVs when they are subjected to external forces caused by the terrain and faulty actuators. A nonlinear model that includes all the factors of wheel-soil interaction, Bekker sinkage, slips, soft-soil resistance, and dynamics of the drive train and battery is built using high fidelity. Multiplicative and additive actuator faults are considered in our discussions. The proposed controller integrates adaptive gain tuning, real-time disturbance estimation, and actuator effectiveness identification. Using Lyapunov stability analysis, it is proven that the sliding variable and velocity tracking error converge to a compact residual set in finite time, while all closed-loop signals remain bounded. Extensive simulations under nominal conditions, severe terrain variations, actuator faults, and stochastic uncertainties demonstrate that the proposed ASTSMC-ESO achieves faster convergence, significantly reduced tracking error, and improved robustness compared with conventional PID and classical sliding mode control. Specifically, the root-mean-square tracking error is reduced by more than 57 % compared with conventional SMC and by more than 73 % compared with PID control. Moreover, the proposed method effectively suppresses chattering and maintains fault-tolerant performance under harsh off-road conditions.
Alsinai et al. (2026) studied this question.