4.6 Article

Flocking of Second-Order Multiagent Systems With Connectivity Preservation Based on Algebraic Connectivity Estimation

Journal

IEEE TRANSACTIONS ON CYBERNETICS
Volume 47, Issue 4, Pages 1067-1077

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2016.2537307

Keywords

Connectivity preservation; distributed consensus; generalized potential fields; inverse power iteration; multiagent systems

Funding

  1. Projects of Major International (Regional) Joint Research Program NSFC [61120106010]
  2. Program for Changjiang Scholars and Innovative Research Team in University [IRT1208]
  3. Changjiang Scholars Program
  4. National Natural Science Foundation of China [61573062, 61304215]
  5. Beijing Education Committee Cooperation Building Foundation Project
  6. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [61321002]
  7. Beijing Outstanding Ph.D. Program Mentor [20131000704]

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The problem of flocking of second-order multiagent systems with connectivity preservation is investigated in this paper. First, for estimating the algebraic connectivity as well as the corresponding eigenvector, a new decentralized inverse power iteration scheme is formulated. Then, based on the estimation of the algebraic connectivity, a set of distributed gradient-based flocking control protocols is built with a new class of generalized hybrid potential fields which could guarantee collision avoidance, desired distance stabilization, and the connectivity of the underlying communication network simultaneously. What is important is that the proposed control scheme allows the existing edges to be broken without violation of connectivity constraints, and thus yields more flexibility of motions and reduces the communication cost for the multiagent system. In the end, nontrivial comparative simulations and experimental results are performed to demonstrate the effectiveness of the theoretical results and highlight the advantages of the proposed estimation scheme and control algorithm.

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