Quadrotor aircraft are drawing considerable attention for their high mobility and capacity to perform tasks with complete autonomy, while minimizing the costs and risks involved with the direct intervention of human operators. Moreover, several limitations characterizing these rotary-wing unmanned aerial systems (UASs), such as their underactuation, make quadrotors ideal testbeds for innovative theoretical approaches to the problem of controlling mechanical systems. Designing autopilots for autonomous quadrotors is a challenging task, which involves multiple interconnected aspects. Numerous researchers are currently addressing the problem of designing autonomous guidance systems, navigation systems, and control systems for quadrotors. The primary goal of this article is to present an analysis and synthesis of several nonlinear robust control systems for quadrotors, as discussed in “Summary.” First, the article presents and analyzes the equations of motion of quadrotors under three sets of progressively restrictive modeling assumptions: 1) the vehicle's inertial properties (such as the mass and matrix of inertia) vary in time, 2) the quadrotor's main frame is a rigid body and the propellers are thin spinning discs, and 3) the pitch and roll angles are small.

This paper presents an innovative control architecture for tilt-rotor quadcopters with H-configuration transporting unknown, sling payloads. This control architecture leverages on a thorough analysis of the aircraft's equation of motion, which reveals gyroscopic effects that were not fully characterized and were disregarded while synthesizing control algorithms in prior publications. Furthermore, the proposed control architecture employs barrier Lyapunov functions and a novel robust model reference adaptive control law to guarantee a priori user-defined constraints on both the trajectory tracking error and the control input, despite poor information on the aircraft's inertial properties and the presence of unknown, unsteady payloads. Flight tests involving a quadcopter pulling an unmodeled cart by means of a thin rope of unknown length, which is slack at the beginning of the mission, verify the effectiveness of the theoretical results.

In classical model reference adaptive control, the closed-loop system’s ability to track a given reference signal can be tuned by choosing the adaptive rates and parameterizing the solution of an algebraic Lyapunov equation that appears in the adaptive law. The projection operator can be employed to impose user-defined constraints on the adaptive gains. However, using the projection operator and quadratic Lyapunov functions to certify uniform ultimate boundedness of the trajectory tracking error, the bounds on the trajectory tracking error can only be estimated, but not explicitly imposed a priori. In this paper, we provide an adaptive control law for the same class of nonlinear dynamical systems as classical model reference adaptive control. A barrier Lyapunov function guarantees that user-defined constraints on both the trajectory tracking error and the adaptive gains are verified.