TY - GEN
T1 - Multi-agent consensus algorithm with obstacle avoidance via optimal control approach
AU - Wang, Jianan
AU - Xin, Ming
PY - 2011
Y1 - 2011
N2 - Multi-agent consensus problem in an obstacle-laden environment is addressed in this paper. A novel optimal control approach is proposed for the multi-agent system to reach consensus as well as avoid obstacles with a reasonable control effort. An innovative nonquadratic penalty function is constructed to achieve obstacle avoidance capability from an inverse optimal control perspective. The asymptotic stability and optimality of the consensus algorithm are proven. In addition, the optimal control law of each agent only requires local information from the neighbors to guarantee the proposed behaviors, rather than all agents' information. The consensus and obstacle avoidance are validated through various simulations.
AB - Multi-agent consensus problem in an obstacle-laden environment is addressed in this paper. A novel optimal control approach is proposed for the multi-agent system to reach consensus as well as avoid obstacles with a reasonable control effort. An innovative nonquadratic penalty function is constructed to achieve obstacle avoidance capability from an inverse optimal control perspective. The asymptotic stability and optimality of the consensus algorithm are proven. In addition, the optimal control law of each agent only requires local information from the neighbors to guarantee the proposed behaviors, rather than all agents' information. The consensus and obstacle avoidance are validated through various simulations.
UR - http://www.scopus.com/inward/record.url?scp=80053154451&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80053154451
SN - 9781457700804
T3 - Proceedings of the American Control Conference
SP - 2783
EP - 2788
BT - Proceedings of the 2011 American Control Conference, ACC 2011
T2 - 2011 American Control Conference, ACC 2011
Y2 - 29 June 2011 through 1 July 2011
ER -