Global tracking control of quadrotor based on adaptive dynamic surface control

Abstract

This paper presents a global nonlinear tracking control system for a quadrotor unmanned aerial vehicle (UAV) in the presence of underactuation, external disturbances and model uncertainties. Quadrotor systems lack enough independent control inputs to control their entire configuration space directly due to underactuation. The proposed solution is to adopt a cascade feedback technique that splits the system dynamics into attitude and position dynamics. The proposed controller is developed directly on the special Euclidean group with a region of attraction covering the entire configuration space where its stability is proven using Lyapunov functions. The controller guarantees the asymptotical convergence of tracking error in the presence of model uncertainties and external disturbances. In particular, the control method combines three techniques: a second-order sliding mode control (SMC), a dynamic surface control, and a non-parametric adaptation mechanism. The SMC is used to stabilize the position dynamics (internal dynamics) by generating a proper attitude command for the attitude controller. The DMC control guarantees the attitude dynamics stability globally and tracking performance while avoiding the mathematical complexities associated with the highly nonlinear dynamics. The adaptation mechanism includes a radial basis function neural network to observe uncertainties without the need for prior training. The uncertainties considered include unmodeled dynamics, external disturbances and parameter uncertainties including the mass and inertial matrices as well as motor coefficients. The desirable features of the proposed control system are illustrated by both numerical simulation and experiments on a UAV testbed.