Containment control for fractional-order networked system with intermittent sampled position communication.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper investigates containment control for fractional-order networked systems. Two novel intermittent sampled position communication protocols, where controllers only need to keep working during communication width of every sampling period under the past sampled position communication of neighbors' agents. Then, some necessary and sufficient conditions are derived to guarantee containment about the differential order, sampling period, communication width, coupling strengths, and networked structure. Taking into account of the delay, a detailed discussion to guarantee containment is given with respect to the delay, sampling period, and communication width. Interestingly, it is discovered that containment control cannot be guaranteed without delay or past sampled position communication under the proposed protocols. Finally, the effectiveness of theoretical results is demonstrated by some numerical simulations.

Authors

  • Yanyan Ye
    Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, and Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
  • Hongzhe Chen
    Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, and Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
  • Jie Tao
    Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China. Electronic address: jtao@iipc.zju.edu.cn.
  • Qianqian Cai
    Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, and Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
  • Peng Shi