Suspended Load Path Tracking Control Using a Tilt-rotor UAV Based on Zonotopic State Estimation

TL;DR

This paper presents a control and estimation framework for a tilt-rotor UAV transporting a suspended load, utilizing a zonotopic state estimator and a robust discrete-time controller to handle nonlinear dynamics and sensor uncertainties.

Contribution

It introduces a novel zonotopic state estimator for load position and orientation, integrated with a robust control scheme for path tracking of suspended loads using tilt-rotor UAVs.

Findings

Zonotopic estimator accurately estimates load state with bounded measurement noise.

The control scheme achieves robust path tracking under uncertainties and disturbances.

Simulation results validate the effectiveness of the proposed methods.

Abstract

This work addresses the problem of path tracking control of a suspended load using a tilt-rotor UAV. The main challenge in controlling this kind of system arises from the dynamic behavior imposed by the load, which is usually coupled to the UAV by means of a rope, adding unactuated degrees of freedom to the whole system. Furthermore, to perform the load transportation it is often needed the knowledge of the load position to accomplish the task. Since available sensors are commonly embedded in the mobile platform, information on the load position may not be directly available. To solve this problem in this work, initially, the kinematics of the multi-body mechanical system are formulated from the load's perspective, from which a detailed dynamic model is derived using the Euler-Lagrange approach, yielding a highly coupled, nonlinear state-space representation of the system, affine in the inputs, with the load's position and orientation directly represented by state variables. A zonotopic state estimator is proposed to solve the problem of estimating the load position and orientation, which is formulated based on sensors located at the aircraft, with different sampling times, and unknown-but-bounded measurement noise. To solve the path tracking problem, a discrete-time mixed $\mathcal{H}_2/\mathcal{H}_\infty$ controller with pole-placement constraints is designed with guaranteed time-response properties and robust to unmodeled dynamics, parametric uncertainties, and external disturbances. Results from numerical experiments, performed in a platform based on the Gazebo simulator and on a Computer Aided Design (CAD) model of the system, are presented to corroborate the performance of the zonotopic state estimator along with the designed controller.