Filter-Based Disturbance Observer and Adaptive Control for Euler–Lagrange Systems With Application to a Quadrotor UAV

Abstract

In this paper, a filter-based control scheme is developed for Euler-Lagrange systems with unknown parameter and external disturbance. Two controllers are proposed under the filtering framework, namely the adaptive controller and the disturbance observer-based controller, respectively. A set of low-pass filters are employed in the control design to derive useful filter outputs, which can provide the design freedom for the parameter estimator or the disturbance observer. For the adaptive controller, a certainty equivalent adaptive law is designed in such way that dominates the cross term between the estimation error and the filtered regression matrix to achieve better performance compared with classical estimators. For the disturbance observer-based controller, a high-gain disturbance observer is constructed for the lumped uncertainty with an arbitrary order for users to determine. Experimental results are presented to verify the effectiveness of the proposed schemes on a quadrotor UAV in several cases.