Abstract

The path following a finless airship is presented in this paper using a nonunified sliding mode-based lateral guidance and control framework. The outer-guidance loop relies on the airship’s kinematics, and the designed sliding surface is based on the leading angle that generates the heading angle reference commands. For the inner-control loop, the sliding surface is designed based on the yaw error angle generating commands by actuating the propulsion arms. The effectiveness of the proposed framework is validated by using a high-fidelity nonlinear simulation along with actuator dynamics and sensor models having measurement noises and external disturbances. The results demonstrate the effectiveness of the proposed design framework compared to the classical techniques using proportional navigation in the outer-guidance loop and a linear quadratic regulator in the inner-control loop.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This work was supported by the Natural Science Foundation of China under Grant 61873017, in part by the Beijing Natural Science Foundation under Grant Z180005.

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Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 35Issue 2March 2022

History

Received: Oct 29, 2020
Accepted: Oct 12, 2021
Published online: Nov 27, 2021
Published in print: Mar 1, 2022
Discussion open until: Apr 27, 2022

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Ph.D. Student, School of Automation and Electrical Engineering, Beihang Univ., Beijing 100191, China. Email: [email protected]
Ph.D. Student, School of Automation and Electrical Engineering, Beihang Univ., Beijing 100191, China. Email: [email protected]
M. Zamurad Shah [email protected]
Researcher, Center of Excellence in Science and Applied Technology (CESAT), 94, Sector H-11/4, Islamabad 44000, Pakistan. Email: [email protected]
Associate Professor, School of Automation and Electrical Engineering, Beihang Univ., Beijing 100191, China (corresponding author). ORCID: https://orcid.org/0000-0002-7014-2149. Email: [email protected]
Qing-Guo Wang [email protected]
Chair Professor, Institute of Artificial Intelligence and Future Networks, Beijing Normal Univ. at Zhuhai, BNU-HKBU United International College, Zhuhai 519087, PR China. Email: [email protected]

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