Trophallaxis network control approach to formation flight of multiple unmanned aerial vehicles

2013 ◽  
Vol 56 (5) ◽  
pp. 1066-1074 ◽  
Author(s):  
HaiBin Duan ◽  
QiNan Luo ◽  
YaXiang Yu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Network Control ◽  
Formation Flight ◽  
Control Approach ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles

Implementation of formation flight of multiple unmanned aerial vehicles

2010 ◽  
Author(s):  
Xiangxu Dong ◽  
Guowei Cai ◽  
Feng Lin ◽  
Ben M. Chen ◽  
Hai Lin ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Flight ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles

Target tracking using multiple unmanned aerial vehicles: Graph theoretic nonlinear control approach

2016 ◽  
Vol 231 (3) ◽  
pp. 570-586 ◽  
Author(s):  
K Subbarao ◽  
M Ahmed
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Target Tracking ◽  
Spanning Tree ◽  
Tracking Errors ◽  
Control Approach ◽  
Graph Theoretic ◽  
Aerial Vehicles ◽  
Flight Path Angle ◽  
Directed Spanning Tree ◽  
Multiple Unmanned Aerial Vehicles

This paper develops a cooperative controller for multiple Unmanned Aerial Vehicles (UAVs) with application to target tracking. The cooperation between the UAVs is established based on an algebraic graph connection and the target information is provided externally by pinning it into a subset of the network. A backstepping-like technique is employed to design a consensus-based controller for each UAV in order to achieve target tracking in 3-D. The proposed controller computes commanded signals for the speed, flight path angle, and heading angle to track the target. The paper considers both the cases of fixed and dynamically changing communication topologies. It is shown that target tracking is achieved for fixed connection topology, if the graph has a directed spanning tree; and for the dynamically changing topology, if the union of the graphs over finite time intervals has a directed spanning tree. The system’s stability is shown using a Lyapunov function-based approach for these cases. All tracking errors are shown to be bounded as long as the target states and its derivatives up to second order are bounded. Detailed numerical simulations further illustrate the controller performance.

Persistent Monitoring by Multiple Unmanned Aerial Vehicles Using Bernstein Polynomials

2021 ◽  
Author(s):  
Calvin Kielas-Jensen ◽  
Venanzio Cichella ◽  
David Casbeer ◽  
Satyanarayana Gupta Manyam ◽  
Isaac Weintraub
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Bernstein Polynomials ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Persistent Monitoring
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