SVSF-Based Robust UGV/UAV Control/Tracking Architecture in Disturbed Environment

This paper presents the design of a robust architecture for the tracking of an unmanned ground vehicle (UGV) by an unmanned aerial vehicle (UAV). To enhance the robustness of the ground vehicle in the face of external disturbances and handle the non-linearities due to inputs saturation, an integral sliding mode controller was designed for the task of trajectory tracking. Stabilization of the aerial vehicle is achieved using an integral-backstepping solution. Estimation of the relative position between the two agents was solved using two approaches: the first solution (optimal) is based on a Kalman filter (KF) the second solution (robust) uses a smooth variable structure filter (SVSF). Simulations results, based on the full non-linear model of the two agents are presented in order to evaluate the performance and robustness of the proposed tracking architecture.

Automated summary

This paper presents a robust architecture design for tracking an unmanned ground vehicle by an unmanned aerial vehicle, including integral sliding mode controller and integral-backstepping solution. Two approaches, Kalman filter and smooth variable structure filter, are used to estimate the relative position between the two agents. Simulation results based on the full non-linear model evaluate the performance and robustness of the proposed tracking architecture.