1066-033X/18©2018IEEE 102 IEEE CONTROL SYSTEMS MAGAZINE » JUNE 2018 » FOCUS ON EDUCATION ANDREA L’AFFLITTO, ROBERT B. ANDERSON, and KEYVAN MOHAMMADI An Introduction to Nonlinear Robust Control for Unmanned Quadrotor Aircraft How to Design Control Algorithms for Quadrotors Using Sliding Mode Control and Adaptive Control Techniques Q uadrotor 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 [1]–[4]. Moreover, several limitations character- izing these rotary-wing unmanned aerial systems (UASs), such as their underactuation, make quadrotors ideal test- beds 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 [5]–[9], navigation systems [10]–[12], 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 analysis is instrumental to both explain the assumptions underlying the dynamical models used in quadrotors’ control systems design and understand the architecture of autopilots for quadrotors. Next, we explain how sliding mode control, model reference adaptive control (MRAC), and adaptive sliding mode control design tech- niques can be applied to create autopilots for quadrotors. These techniques were chosen over others for their popu- larity and relative ease of implementation. Finally, we show a qualitative and quantitative approach to the problem of selecting a nonlinear robust control law for quadrotors. As part of this selection process, the performances of sliding mode control, MRAC, and adaptive sliding mode control laws are evaluated, compared, and contrasted through numerical simulations. The most promising of these control laws for precision, robustness, and computational time is successively implemented and tested on a quadrotor. This article targets both control practitioners and engi- neering students who have been exposed to graduate-level courses in the analysis and control of nonlinear dynamical systems. Both sliding mode control and model reference adaptive control are illustrated by explicitly referencing graduate-level textbooks such as [13] and [14] so that the problem of designing autopilots for quadrotors results in a direct application of the theoretical notions usually pre- sented in class. The adaptive sliding mode control tech- nique is presented to illustrate how a significant limitation Date of publication: 18 May 2018 Digital Object Identifier 10.1109/MCS.2018.2810559 Summary I n the near future, quadrotor vehicles will be involved in many complex tasks, such as transporting injured people from secluded locations or manipulating objects in indus- trial premises. These mission scenarios require exploiting the quadrotors’ ability to operate in the proximity of people and obstacles, be robust to adverse weather and malfunc- tions of the propulsion system, and guarantee the safety of their payloads. These strict requirements can be met by employing nonlinear robust control algorithms to design au- topilots for quadrotors. This article is aimed both at control practitioners and engineering students who have been ex- posed to graduate-level courses in the analysis and control of nonlinear dynamical systems. It presents, in a tutorial manner, how sliding mode control, model reference adap- tive control, and adaptive sliding mode control can be ap- plied to design autopilots for quadrotors that are robust to model uncertainties, external disturbances, sensor noises, and faults of the control system. Numerical examples and experimental results are used to illustrate both the appli- cability of the theoretical results and the performances of control algorithms presented. The numerical examples have been produced using the open-source virtual simula- tor Matlab/Simulink A Simulator for Quadrotors, created by the authors.