Output Regulation of Nonlinear Multi-agent Systems Based on Dynamic Neural Networks

摘要：

In this paper, the output regulation problem of the nonlinear multi-agent system with dynamic neural networks is addressed. First, we use a neural network to approximate the nonlinear model of the considered multi-agent system by the learning law. Then the output regulation technique is used to the neural network to design a controller, which make the following agents to asymptotically track (or reject) the reference (or disturbance) generated by an exosystem. The exosystem can be viewed as the active leaders or the environmental disturbance in the multi-agent systems. Finally, a numerical simulation example is presented to demonstrate the effectiveness of the main results.

关键词： Multi-agent Systems Output Regulation Problem Dynamic Neural Networks Active Leader Coordinative Control

作者: Jia Liu Zengqiang Chen Zhongxin Liu Peng Yang

作者单位: Department of Automation, Nankai University, Tianjin 300071 School of Control Science and Engineering, Hebei University of Technology, Tianjin 300013, P.R.China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 6059-6064

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）