Adaptive augmentation of the attitude control system for a multirotor unmanned aerial vehicle

Abstract

In this paper, the adaptive augmentation of the attitude control system for a multirotor unmanned aerial vehicle is considered. The proposed approach allows to combine a baseline controller with an adaptive one and to disable or enable the adaptive controller when needed, in order to take the advantages of both the controllers. To improve transient performance with respect to the standard model reference adaptive controller, an observed-based approach is exploited. The adaptation law is based on the error between the output of an observer of the nominal closed-loop dynamics and the actual output of the system with uncertainties. Experimental results obtained by testing the proposed approach on a quadrotor unmanned aerial vehicle are presented to compare the performance, in terms of disturbance rejection, with respect to the baseline controller and to a [Formula: see text] adaptive augmentation scheme.

Robust Tuning of Geometric Attitude Controllers for Multirotor Unmanned Aerial Vehicles

“…As can be seen from equation (10), the coplanar propellers UAV is an underactuated mechanical system: no force can be instantaneously delivered in the plane spanned by 1 , 2 . To control position, the standard approach assumes full actuation of the attitude subsystem to stabilize the position error dynamics.…”

“…In practice, a control law for is designed to tilt the body vector 3 in the direction of the force required for position tracking. At the same time, the magnitude of the control force is adjusted to match the magnitude of the required force and then the propellers thrust (input ) is computed by inverting (10). Therefore, the design of control laws for attitude tracking becomes a fundamental ingredient to ensure the stability of the overall system.…”

“…for some bounded torque and thrust according to the (right) pseudo inverse of (10). In such a case, since sat…”

“…experience. An alternative solution to deal with such issue is to develop nonlinear adaptive schemes which, nonetheless, results in a more complex control law [10][11][12].…”

Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

“…27 Among them, adaptive control system is an invaluable and efficient approach to handle a wide variety of systems. [28][29][30][31][32] To achieve autonomy and waypoint following, model reference adaptive control scheme based on linear model of quadcopter was presented. 33 By neglecting gyroscopic effects of the body of the quadcopter, a single-input single-output dynamic model was used to design gain-scheduled PID control.…”