Quadrotor UAV Elastically Attached to Uncertain Payload: Trajectory Control and Vibrations Suppression

Quadrotor Unmanned Aerial Vehicles (UAVs) are a promising configuration in the context of Unmanned Aircraft System (UAS) technology as they can be effectively used for a variety of tasks in terms of the development of innovative aerial transportation systems, e.g. last-mile delivery and transportation of medical samples. In applications with payload transportation, the vibrations induced during the flight pose significant challenges, potentially compromising the flight stability and the integrity of the payload (e.g. these issues become critical in certain applications such as the transportation of medical samples). Thus, the accurate modeling and evaluation of these vibrations are essential to ensure reliable operations. This paper describes the design of a Sliding Mode Control (SMC) strategy with parametric uncertainties and optimized gains for controlling a quadrotor carrying a payload, when a flexible attachment link is assumed between both systems. The effects of both the payload and the flexibility of the attachment link on the system dynamics are investigated. Moreover, the Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) are combined for tuning the gains of the sliding mode controller in a shorter computational time. In this sense, we propose to use the GA with fewer iterations than the convergence, and then finalize the optimization with an additional efficient and lower computational time procedure (SQP). Since lower oscillations are required, the objective function is designed based on the relative trajectory minimum oscillations intensity is required of the payload’s vibrations and their uncertainties. The simulation results obtained using MATLAB/Simulink corroborate the validity of the approach, which allows the quadrotor platform to track a reference trajectory while containing the oscillations of the payload. Also, the proposed control approach accounts for payload’s parametric uncertainties regarding payload mass and payload inertia values.

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Publication Details

Journal
Unmanned Systems
Published
2025-04-24
DOI
https://doi.org/10.1142/s2301385026500408
Citations
2
Primary Topic
Control and Dynamics of Mobile Robots
Type
article
Field-Weighted Citation Impact
2.43
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article

Quadrotor UAV Elastically Attached to Uncertain Payload: Trajectory Control and Vibrations Suppression

Renan Sanches Geronel, Marco Rinaldi, Maíra Martins da Silva, Stefano Primatesta
2 citations
Unmanned Systems
Control and Dynamics of Mobile Robots
2.43
article

Quadrotor UAV Elastically Attached to Uncertain Payload: Trajectory Control and Vibrations Suppression

Renan Sanches Geronel, Marco Rinaldi, Maíra Martins da Silva, Stefano Primatesta
article en
2 citations

Abstract

Quadrotor Unmanned Aerial Vehicles (UAVs) are a promising configuration in the context of Unmanned Aircraft System (UAS) technology as they can be effectively used for a variety of tasks in terms of the development of innovative aerial transportation systems, e.g. last-mile delivery and transportation of medical samples. In applications with payload transportation, the vibrations induced during the flight pose significant challenges, potentially compromising the flight stability and the integrity of the payload (e.g. these issues become critical in certain applications such as the transportation of medical samples). Thus, the accurate modeling and evaluation of these vibrations are essential to ensure reliable operations. This paper describes the design of a Sliding Mode Control (SMC) strategy with parametric uncertainties and optimized gains for controlling a quadrotor carrying a payload, when a flexible attachment link is assumed between both systems. The effects of both the payload and the flexibility of the attachment link on the system dynamics are investigated. Moreover, the Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) are combined for tuning the gains of the sliding mode controller in a shorter computational time. In this sense, we propose to use the GA with fewer iterations than the convergence, and then finalize the optimization with an additional efficient and lower computational time procedure (SQP). Since lower oscillations are required, the objective function is designed based on the relative trajectory minimum oscillations intensity is required of the payload’s vibrations and their uncertainties. The simulation results obtained using MATLAB/Simulink corroborate the validity of the approach, which allows the quadrotor platform to track a reference trajectory while containing the oscillations of the payload. Also, the proposed control approach accounts for payload’s parametric uncertainties regarding payload mass and payload inertia values.

Unmanned Systems
Politecnico di Torino (IT), Universidade de São Paulo (BR)
Affordable and clean energy
Openalex Percentile: Top 12%
Control and Dynamics of Mobile Robots
2.43
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