TY - GEN
T1 - Distributed Optimization of Nonlinear Multi-Agent Systems
T2 - 58th IEEE Conference on Decision and Control, CDC 2019
AU - Liu, Tengfei
AU - Qin, Zhengyan
AU - Hong, Yiguang
AU - Jiang, Zhong Ping
N1 - Funding Information:
*This work was supported in part by NSFC grants 61522305, 61633007, 61533007 and 61733018, in part by NSF grant ECCS-1501044, and in part by State Key Laboratory of Intelligent Control and Decision of Complex Systems at BIT.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - This paper studies the distributed optimal output agreement problem for multi-agent systems described by uncertain nonlinear models. By using 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 paper introduces distributed coordinators to calculate the ideal outputs, and designs reference-tracking controllers for the agents to follow the ideal outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multi-agent system is considered as a dynamical network, and Sontag's input-to-state stability (ISS) properties are employed to characterize the interconnections. It is shown that output agreement in multi-agent nonlinear systems is achievable by means of distributed optimal coordinators via a small-gain approach. Numerical simulations are employed to show the effectiveness of the design.
AB - This paper studies the distributed optimal output agreement problem for multi-agent systems described by uncertain nonlinear models. By using 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 paper introduces distributed coordinators to calculate the ideal outputs, and designs reference-tracking controllers for the agents to follow the ideal outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multi-agent system is considered as a dynamical network, and Sontag's input-to-state stability (ISS) properties are employed to characterize the interconnections. It is shown that output agreement in multi-agent nonlinear systems is achievable by means of distributed optimal coordinators via a small-gain approach. Numerical simulations are employed to show the effectiveness of the design.
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U2 - 10.1109/CDC40024.2019.9030142
DO - 10.1109/CDC40024.2019.9030142
M3 - Conference contribution
AN - SCOPUS:85082448941
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5252
EP - 5257
BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2019 through 13 December 2019
ER -