Abstract
In multiple unmanned aerial vehicle (UAV) formation control systems, high scalability can guarantee the formation stability when UAVs join in or leave the system, and thus improves the robustness of the formation flight. This paper investigates the scalability problem for multi-UAV formation control with double-integrator dynamics. To be more specific, we focus how to build communication links with fixed control parameters such that the formation can always keep stable when adding/removing arbitrary number of UAVs. A bio-inspired method - Veteran Rule is proposed to solve this problem. Compared to the existing methods, our proposed method does not require to re-design or adaptively adjust the control parameters/gains for the changed Laplacian matrix. Furthermore, the convergence rate of the system under the Veteran Rule is analyzed. Surprisingly, the convergence rate of the system reaches the maximum value when all the in-degrees equal a particular value, rather than goes to infinity. Moreover, to guarantee the robustness of the formation system, we study the tolerance on undesired communication links (which break our proposed Veteran Rule). An upper bound for the coupling strength of the undesired communication links is provided by using Gershgorin circle theorem. Finally, simulation results corroborate the effectiveness of our results.
Highlights
OUR CONTRIBUTIONS In this work, we study the scalability problem for the unmanned aerial vehicle (UAV) formation governed by double-integrator dynamics under a directed communication topology
This result, the Veteran Rule with optimal convergence rate is proposed. iii) To guarantee the robustness of the formation system, we study the tolerance on undesired communication links, i.e., reverse edges
We study the scalability problem for formation control that without changing control parameter γ, how to design the communication links as well as their strengths such that: i) The formation system is still stable after adding new UAVs, i.e., the system has scalability; ii) The convergence rate of the formation error is maximized; Note that the scalability does not intrinsically hold in formation systems
Summary
B. RELATED WORKS In algebraic-graph-based formation control framework, consensus is a commonly used method, which means in a typical multi-agent system, each agent shares information only with its neighboring agents under a designed protocol while the whole group can coordinate to achieve a certain global behavior [10]. RELATED WORKS In algebraic-graph-based formation control framework, consensus is a commonly used method, which means in a typical multi-agent system, each agent shares information only with its neighboring agents under a designed protocol while the whole group can coordinate to achieve a certain global behavior [10] This has resulted in tremendous amount of interest for this topic, and two pioneer papers on consensus problem are [11], [12].
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