Model Predictive Landing Control of an Unmanned Aerial Vehicle via Partial Feedback Linearization

Abstract

This paper introduces a model predictive control approach of an unmanned aerial vehicle (UAV) with the aid of a feedback linearization. As is well known, the feedback linearization is one of the effective techniques to cope with the nonlinearity of dynamical systems. Since the UAV is an underactuated nonlinear system, it is impossible to exactly linearize the dynamics of the UAV. Therefore, we take an approach to linearize only the translational motion, and then apply the linear optimal control to it. However, the UAV is easily affected by wind disturbances in an actual environment. A model predictive control is proposed to cope with the disturbances. We apply this approach to a landing control of the UAV to a moving ground vehicle. The effectiveness of the proposed method is verified by numerical simulations.