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Research paper

An Input–Output Feedback Linearization-Based Exponentially Stable Controller for Multi-UAV Payload Transport

Nishanth Rao ( )Suresh Sundaram 
Department of Aerospace Engineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, India

This paper was recommended for publication in its revised form by editorial board member, Jinwen Hu.

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Abstract

In this paper, an exponentially stable trajectory tracking controller is proposed for multi-UAV payload transport. The multi-UAV payload system has a 2-DOF magnetic spherical joint between the UAVs and the vertical rigid links of the payload frame so that the UAVs can roll or pitch freely. These vertical links are rigidly attached to the payload and cannot move. An input–output feedback linearized model is derived for the complete payload-UAV system along with thrust vectoring control for trajectory tracking of the payload. Theoretical analysis of tracking control laws is shown to be exponentially stable, thus guaranteeing safe transportation along the desired trajectory. To validate the performance of the proposed control law, the results for a numerical simulation as well as a high-fidelity Gazebo real-time simulation are presented. The tracking performance is compared to the existing techniques in the literature, and it is seen that the proposed approach has the least RMSE for tracking performance. Next, the robustness of the proposed controller is analyzed against two practical situations: External disturbance on the payload and payload mass uncertainty. The results clearly indicate that the proposed controller is robust and computationally efficient while achieving exponentially stable trajectory tracking.

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Unmanned Systems
Pages 521-539

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Cite this article:
Rao N, Sundaram S. An Input–Output Feedback Linearization-Based Exponentially Stable Controller for Multi-UAV Payload Transport. Unmanned Systems, 2025, 13(2): 521-539. https://doi.org/10.1142/S2301385025500311

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Received: 24 July 2023
Revised: 24 February 2024
Accepted: 24 February 2024
Published: 25 April 2024
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