TY - JOUR
T1 - Distributed Optimization of Nonlinear Multiagent Systems
T2 - A Small-Gain Approach
AU - Liu, Tengfei
AU - Qin, Zhengyan
AU - Hong, Yiguang
AU - Jiang, Zhong Ping
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant U1911401, Grant 61733018, and Grant 61633007, in part by the Science and Technology Major Special Plan of Liaoning Province under Grant 2020JH1/10100008, in part by the Consulting Research Project of the Chinese Academy of Engineering under Grant 2019-XZ-7, and in part by the U.S. National Science Foundation under Grant EPCN-1903781.
Publisher Copyright:
© 1963-2012 IEEE.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - This article studies the distributed optimal output agreement problem for multiagent systems described by uncertain nonlinear models. By using the partial information of an objective function, the design aims to steer the outputs of the agents to an agreement on the optimal solution to the objective function. To solve this problem, this article introduces distributed coordinators to calculate the desired outputs, and designs reference-tracking controllers for the agents to follow the desired outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multiagent system is considered as a dynamical network, and Sontag's input-to-state stability is employed to characterize the interconnections. It is shown that output agreement in multiagent nonlinear systems is achievable by means of distributed optimal controllers via a small-gain approach. The proposed design features a three-layer architecture, and the reference-tracking controllers can be implemented as successive nonlinear proportional-integral loops. A numerical example is employed to show the effectiveness of the design.
AB - This article studies the distributed optimal output agreement problem for multiagent systems described by uncertain nonlinear models. By using the partial information of an objective function, the design aims to steer the outputs of the agents to an agreement on the optimal solution to the objective function. To solve this problem, this article introduces distributed coordinators to calculate the desired outputs, and designs reference-tracking controllers for the agents to follow the desired outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multiagent system is considered as a dynamical network, and Sontag's input-to-state stability is employed to characterize the interconnections. It is shown that output agreement in multiagent nonlinear systems is achievable by means of distributed optimal controllers via a small-gain approach. The proposed design features a three-layer architecture, and the reference-tracking controllers can be implemented as successive nonlinear proportional-integral loops. A numerical example is employed to show the effectiveness of the design.
KW - Input-to-state stability (ISS)
KW - Multiagent systems
KW - Nonlinear proportional-integral (PI) control
KW - Nonlinear uncertain dynamics
KW - Optimal output agreement
UR - http://www.scopus.com/inward/record.url?scp=85100465132&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100465132&partnerID=8YFLogxK
U2 - 10.1109/TAC.2021.3053549
DO - 10.1109/TAC.2021.3053549
M3 - Article
AN - SCOPUS:85100465132
VL - 67
SP - 676
EP - 691
JO - IRE Transactions on Automatic Control
JF - IRE Transactions on Automatic Control
SN - 0018-9286
IS - 2
ER -