Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle

Abstract

This paper addresses the stability and tracking control problem of miniature unmanned multirotor aerial vehicle (MUMAV) in the presence of bounded uncertainty. The uncertainty may appear from unmodeled dynamics, underactuated property, input disturbance and flying environment. Nonlinear robust adaptive sliding mode control algorithm is designed by using Lyapunov function. Robust adaptation laws are designed to learn and compensate the bounded parametric uncertainty. Lyapunov analysis shows that the proposed algorithms can guarantee asymptotic stability and tracking control property of the linear and angular dynamics of MUMAV system. Compared with other existing control methods, the proposed design is very simple and easy to implement as it does not require multiple design steps, augmented auxiliary signals and exact bound of the uncertainty. Experimental results on a miniature unmanned quadrotor aerial vehicle are presented to illustrate of effectiveness of the proposed design for real-time applications.