Abstract
Unmanned aerial vehicles (UAV) are becoming more and more widely used and playing an increasingly important role in lots of military and civilian tasks. This paper presents a leader selection algorithm of formation based on rotor UAVs. We assume that a certain UAV is the leader, and use it as a benchmark to convert the state of multiple UAVs into the relative motion state of the leader in this algorithm. The purpose is to select a suitable leader for the formation of UAVs and minimize the time of forming a target formation. In order to solve these problems, we use the linear quadratic regulator (LQR) algorithm to realize the formation control of the UAVs. We also solve the combined mapping problem between the UAVs and target formations which is a sub-problem of leader selection. Finally, the simulation experiments show the processes of UAVs formation. The numerical results further verify the effectiveness of this algorithm.
Supported by National Defense Science and Technology Innovation Zone Foundation under Grant No. 19-163-16-ZD-022-001-01, the Fund of Prospective Layout of Scientific Research for NUAA (Nanjing University of Aeronautics and Astronautics), the Foundation of Key Laboratory of Safety-Critical Software (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology (No. NJ2020022), and also supported by National Natural Science Foundation of China (No. 61701231).
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Liu, B., Zhai, X.B., Du, B., Zhu, J. (2022). Formation Control Optimization via Leader Selection for Rotor Unmanned Aerial Vehicles. In: Zhang, H., et al. Neural Computing for Advanced Applications. NCAA 2022. Communications in Computer and Information Science, vol 1637. Springer, Singapore. https://doi.org/10.1007/978-981-19-6142-7_4
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DOI: https://doi.org/10.1007/978-981-19-6142-7_4
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