TY - JOUR
T1 - Distributed leader-follower flocking control for multi-agent dynamical systems with time-varying velocities
AU - Yu, Wenwu
AU - Chen, Guanrong
AU - Cao, Ming
PY - 2010/9
Y1 - 2010/9
N2 - Using tools from algebraic graph theory and nonsmooth analysis in combination with ideas of collective potential functions, velocity consensus and navigation feedback, a distributed leaderfollower flocking algorithm for multi-agent dynamical systems with time-varying velocities is developed where each agent is governed by second-order dynamics. The distributed leaderfollower algorithm considers the case in which the group has one virtual leader with time-varying velocity. For each agent i, this algorithm consists of four terms: the first term is the self nonlinear dynamics which determines the final time-varying velocity, the second term is determined by the gradient of the collective potential between agent i and all of its neighbors, the third term is the velocity consensus term, and the fourth term is the navigation feedback from the leader. To avoid an impractical assumption that the informed agents sense all the states of the leader, the new designed distributed algorithm is developed by making use of observer-based pinning navigation feedback. In this case, each informed agent only has partial information about the leader, yet the velocity of the whole group can still converge to that of the leader and the centroid of those informed agents, having the leader's position information, follows the trajectory of the leader asymptotically. Finally, simulation results are presented to demonstrate the validity and effectiveness of the theoretical analysis. Surprisingly, it is found that the local minimum of the potential function may not form a commonly believed α lattice. © 2010 Elsevier B.V. All rights reserved.
AB - Using tools from algebraic graph theory and nonsmooth analysis in combination with ideas of collective potential functions, velocity consensus and navigation feedback, a distributed leaderfollower flocking algorithm for multi-agent dynamical systems with time-varying velocities is developed where each agent is governed by second-order dynamics. The distributed leaderfollower algorithm considers the case in which the group has one virtual leader with time-varying velocity. For each agent i, this algorithm consists of four terms: the first term is the self nonlinear dynamics which determines the final time-varying velocity, the second term is determined by the gradient of the collective potential between agent i and all of its neighbors, the third term is the velocity consensus term, and the fourth term is the navigation feedback from the leader. To avoid an impractical assumption that the informed agents sense all the states of the leader, the new designed distributed algorithm is developed by making use of observer-based pinning navigation feedback. In this case, each informed agent only has partial information about the leader, yet the velocity of the whole group can still converge to that of the leader and the centroid of those informed agents, having the leader's position information, follows the trajectory of the leader asymptotically. Finally, simulation results are presented to demonstrate the validity and effectiveness of the theoretical analysis. Surprisingly, it is found that the local minimum of the potential function may not form a commonly believed α lattice. © 2010 Elsevier B.V. All rights reserved.
KW - Algebraic graph theory
KW - Collective potential function
KW - Flocking algorithm
KW - Multi-agent dynamical system
KW - Nonsmooth analysis
KW - Pinning feedback
KW - Velocity consensus
UR - http://www.scopus.com/inward/record.url?scp=77956395472&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-77956395472&origin=recordpage
U2 - 10.1016/j.sysconle.2010.06.014
DO - 10.1016/j.sysconle.2010.06.014
M3 - RGC 21 - Publication in refereed journal
VL - 59
SP - 543
EP - 552
JO - Systems and Control Letters
JF - Systems and Control Letters
SN - 0167-6911
IS - 9
ER -