High-Gain Disturbance Observer for Robust Trajectory Tracking of Quadrotors
Mohammadreza Izadi, Reza Faieghi
TL;DR
This work tackles robustness in quadrotor trajectory tracking under external disturbances by introducing a simple high-gain disturbance observer (HGDO) that yields real-time estimates ${\hat{\bf d}}_1$, ${\hat{\bf d}}_2$ converging to the true disturbances ${\bf d}_1$, ${\bf d}_2$ within an adjustable neighborhood. The HGDO is integrated with a Lyapunov-based controller, exemplified by sliding mode control (SMC), and backed by convergence and stability analyses showing bounded tracking errors. The authors derive an HGDO formulation with auxiliary variables to mitigate noise, establish an error bound ${\|\tilde{\bf d}_i\|} \le \varepsilon_i( {\|\tilde{\bf d}_i(0)\| + \delta_i } )$, and prove that the closed-loop system remains stable under appropriate gain conditions. Through simulations and hardware experiments (Crazyflie 2.1), the HGDO+SMC approach demonstrates faster disturbance estimation and significantly improved trajectory tracking under wind and ground-effect disturbances compared to SMC-only and other disturbance-observer schemes, highlighting its potential as a simple, scalable augmentation to quadrotor controllers.
Abstract
This paper presents a simple method to boost the robustness of quadrotors in trajectory tracking. The presented method features a high-gain disturbance observer (HGDO) that provides disturbance estimates in real-time. The estimates are then used in a trajectory control law to compensate for disturbance effects. We present theoretical convergence results showing that the proposed HGDO can quickly converge to an adjustable neighborhood of actual disturbance values. We will then integrate the disturbance estimates with a typical robust trajectory controller, namely sliding mode control (SMC), and present Lyapunov stability analysis to establish the boundedness of trajectory tracking errors. However, our stability analysis can be easily extended to other Lyapunov-based controllers to develop different HGDO-based controllers with formal stability guarantees. We evaluate the proposed HGDO-based control method using both simulation and laboratory experiments in various scenarios and in the presence of external disturbances. Our results indicate that the addition of HGDO to a quadrotor trajectory controller can significantly improve the accuracy and precision of trajectory tracking in the presence of external disturbances.