@inproceedings{5b5ac06f1f0b4f1388a2152727696a14,
title = "Adaptive neural network control for consensus of nonlinear multi-agent systems with actuator faults",
abstract = "![CDATA[This paper investigates the fault tolerant consensus problem for a class of nonlinear multi-agent systems with actuator faults. The dynamics of the multi-agent systems are unknown nonlinear and nonidentical. The types of actuator fault include partial loss of effectiveness fault and biased fault. The main idea of the fault tolerant control adopted in this paper is the adaptive control. The control method used is a neural network based adaptive control which has a better adaptability than the traditional adaptive control. The developed adaptive neural network consensus protocol is proved to perform well with respect to the system nonlinear dynamics and actuator faults of the agent. Finally, numerical simulation on multi-agent system of four Chen's chaotic systems is performed to illustrate the effectiveness of the investigated adaptive neural network consensus protocol.]]",
keywords = "actuators, adaptive control systems, intelligent agents (computer software), neural networks (computer science), reliability",
author = "Gaosheng Zhang and Qichao Ma and Jiahu Qin and Yu Kang and Zheng, {Wei Xing}",
year = "2018",
doi = "10.1109/ICIST.2018.8426082",
language = "English",
isbn = "9781538637821",
publisher = "IEEE",
pages = "409--414",
booktitle = "Proceedings of the 8th International Conference on Information Science and Technology (ICIST 2018), 30 June-6 July 2018, Cordoba, Granada, and Seville, Spain",
note = "International Conference on Information Science and Technology ; Conference date: 30-06-2018",
}