David Du Mutel de Pierrepont Franzetti, Iris (Universidad Politécnica de Cataluña), Carminati, Davide (Politecnico di Torino), Scanavino, Matteo (Politecnico di Torino), Capello, Elisa (Politecnico di Torino)

Model-In-The-Loop Testing of Control Systems and Path Planner Algorithms for QuadRotor UAVs

Scheduled for presentation during the Regular Session "Simulation" (FrD2), Friday, September 4, 2020, 17:50−18:10, Kozani

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on April 25, 2024

Abstract

Real systems, as Unmanned Aerial Vehicles (UAVs), are usually subject to disturbances and parametric uncertainties, which could compromise the mission accomplishment, considering in particular harsh environment or challenges applications. For this reason, the main idea proposed in this research is the design of the on-board software, as autopilot software candidate, for a multirotor UAV. In detail, the inner loop of the autopilot system is designed with a variable structure control system, based on sliding mode theory, able to handle external disturbances and uncertainties. This controller is compared with a simple Proportional-Integral-Derivative controller, usually implemented on the on-board software. The key aspects of the proposed methodology are the robustness to bounded disturbances and parametric uncertainties of the proposed combination of guidance and control algorithms. A path-following algorithm is designated for the guidance task, which provides the desired waypoints to the control algorithm. Model-in-the-loop simulations have been performed to validate the proposed approaches. Computational efficient algorithms are proposed, as combination of a robust control system and path planner. Extensive simulations are performed to show the effectiveness of the proposed methodologies, considering both disturbances and uncertainties.