Improved robust integral sliding mode control for quadrotor UAV path-planning with a momentum-based estimator

Abstract

Quadrotor unmanned aerial vehicles (QUAVs) are highly non-linear and coupled multi-body systems subject to unknown disturbances and unmodeled dynamics that significantly degrade trajectory tracking performance. These challenges motivate the development of robust and high-performance control strategies. This paper proposed a robust control framework integrating the integral sliding mode controller (ISMC) with a momentum-based estimator (MBE) to ensure accurate trajectory tracking under uncertainty. The proposed control scheme adopts a cascaded control structure, where an inner-loop ISMC regulate the attitude dynamics and an outer-loop ISMC controls the position. To further enhance robustness, the MBE is incorporated to estimate external disturbances and parameters for compensating the unmodulated dynamics in real-time. A Lyapunov-based analysis is provided to guarantee closed-loop stability and convergence in the presence of bounded disturbances. Comprehensive simulation studies involving multiple path-tracking scenarios demonstrate the robustness and efficiency of the proposed approach. In addition, a comparative evaluation with classical strategies, including PID, LQR, and conventional SMC, highlights the superiority of the proposed ISMC-MBE framework in terms of tracking accuracy, convergence speed, and disturbance rejection. Notably, the proposed ISMC alone maintains stability under up to 50% mass uncertainty, while the integration of the MBE significantly improves performance by reducing the peak position error from 3.0 × 10⁻ 3 m to 2.2 × 10⁻ 4 m and the yaw tracking error from 2.0 × 10⁻ 2  rad to 1.2 × 10⁻ 4 rad under unmatched disturbances.