Dual time-scale decoupled fault-tolerant control for quadrotor UAV: a hybrid adaptive sliding mode approach with prescribed-time preset performance

Abstract This paper addresses the control challenges of quadrotor unmanned aerial vehicles (UAVs) under external disturbances, modeling uncertainties, and actuator faults. A dual time-scale decoupled prescribed-time preset performance sliding mode adaptive hybrid fault-tolerant control strategy is proposed. First, the quadrotor system is decoupled into position and attitude dual-loop subsystems. For the outer position loop, a high-order sliding mode observer (HOSMO) estimates lumped disturbances. It is combined with a nonsingular fast integral terminal sliding surface and an adaptive proportional integral derivative (PID) controller. This combination constrains tracking errors using prescribed-time preset performance functions. Simultaneously, an adaptive radial basis function (RBF) neural network and super-twisting sliding mode composite compensator are employed. They suppress chattering and compensate for observer errors. For the inner attitude loop, a simplified sliding mode adaptive composite PID structure is used to conserve computational resources. A composite compensator is applied to reject disturbances and mitigate chattering. Second, Lyapunov analysis rigorously proves the prescribed-time convergence of the position system. It also proves the finite-time convergence of the attitude system. Finally, the results demonstrate that under conditions of intense stochastic disturbances and actuator faults, compared with traditional algorithms, the proposed algorithm can reduce the mean square tracking error by 80%–90%, maintain the preset performance bounds throughout the whole process, and achieve a substantial improvement in computational efficiency. Ablation studies show a further 5%–30% decrease in dynamic error over simplified algorithms, verifying its fault-tolerant capability under biased actuator faults and intensive random disturbances.