@inproceedings{40280b823cbf4729be6e68d045f7a993,
title = "Leader-Following Constrained Distributed Adaptive Dynamic Programming Design for Multiagent Systems",
abstract = "This paper gives an adaptive dynamic programming (ADP)-based distributed adaptive control scheme to solve the cooperative control problem with input constraints. To compensate the effects of the constrained-input, a proper nonquadratic functional is selected to encode the saturation nonlinearity into the optimization formulation. By constructing the single network to estimate the solution of coupled nonlinear Hamilton-Jacobi-Bellman (HJB) equation, distributed cooperative optimal control law can be obtained, which can make the nonzero-sum (NZS) games reach the Nash equilibrium. In addition, the updating law of each NN is designed and implemented simultaneously. Finally, the local consensus error and the estimation error of the NN weight are proved to be boundedness. A numerical simulation is given to verify the effectiveness of the developed method.",
keywords = "Distributed control, adaptive dynamic programming (ADP), differential game, input constraints, multi-agent system",
author = "Ruping Zou and Jing Sun and Jingliang Sun and Teng Long and Along Wei",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Chinese Automation Congress, CAC 2019 ; Conference date: 22-11-2019 Through 24-11-2019",
year = "2019",
month = nov,
doi = "10.1109/CAC48633.2019.8996626",
language = "English",
series = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5345--5349",
booktitle = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",
address = "United States",
}