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Biologically-Inspired Intelligent Flocking Control for Networked Multi-UAS with Uncertain Network Imperfections

by Mohammad Jafari 1,* and Hao Xu 2
1
Department of Applied Mathematics, Jack Baskin School of Engineering, University of California, Santa Cruz, CA 95064, USA
2
Department of Electrical and Biomedical Engineering, University of Nevada, Reno, NV 89557, USA
*
Author to whom correspondence should be addressed.
Drones 2018, 2(4), 33; https://doi.org/10.3390/drones2040033
Received: 26 July 2018 / Revised: 15 September 2018 / Accepted: 27 September 2018 / Published: 29 September 2018
In this paper, a biologically-inspired distributed intelligent control methodology is proposed to overcome the challenges, i.e., networked imperfections and uncertainty from the environment and system, in networked multi-Unmanned Aircraft Systems (UAS) flocking. The proposed method is adopted based on the emotional learning phenomenon in the mammalian limbic system, considering the limited computational ability in the practical onboard controller. The learning capability and low computational complexity of the proposed technique make it a propitious tool for implementing in real-time networked multi-UAS flocking considering the network imperfection and uncertainty from environment and system. Computer-aid numerical results of the implementation of the proposed methodology demonstrate the effectiveness of this algorithm for distributed intelligent flocking control of networked multi-UAS. View Full-Text
Keywords: networked multi-unmanned aircraft systems; flocking control; intelligent control; biologically-inspired reinforcement learning networked multi-unmanned aircraft systems; flocking control; intelligent control; biologically-inspired reinforcement learning
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Jafari, M.; Xu, H. Biologically-Inspired Intelligent Flocking Control for Networked Multi-UAS with Uncertain Network Imperfections. Drones 2018, 2, 33.

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