A Tube-based Robust MPC for a Fixed-wing UAV: an Application for Precision Farming

TL;DR

This paper presents a tube-based robust Model Predictive Control (MPC) for fixed-wing UAVs, enhancing precision farming by ensuring stability and robustness against wind disturbances and model uncertainties, demonstrated through hardware-in-the-loop tests.

Contribution

It introduces a robust guidance and control algorithm for fixed-wing UAVs tailored for precision agriculture, combining robustness with low computational effort.

Findings

Effective disturbance rejection demonstrated in hardware-in-the-loop tests

Maintains stability and repeatability in crop monitoring tasks

Reduces monitoring costs and improves system robustness

Abstract

The techniques of precision agriculture include the possibility to execute crop monitoring tasks through the application of Unmanned Aerial Vehicles (UAVs). These platforms are flexible, easy to use and low-cost, and they are the best candidates for improving the farm efficiency and productivity. In this research, a guidance algorithm and a robust control system are combined to guarantee the robustness of the system to additive noise (i.e. wind disturbance) and uncertainties (i.e. model parameter variations). A small fixed-wing UAV with an autonomy of about $1$ hour is proposed as case study, to reduce the cost of monitoring and increasing the stability performance of the system. A waypoint-grid on a paddy field is verified by hardware-in-the loop tests. The control scheme provides good results with a low computational effort, guaranteeing the repeatability of the monitoring and reduction of the costs.