Finite-Time Distributed Average Tracking for Second-Order Nonlinear Systems. Academic Article uri icon


  • This paper studies the distributed average tracking (DAT) problem for multiple reference signals described by the second-order nonlinear dynamical systems. Leveraging the state-dependent gain design and the adaptive control approaches, a couple of DAT algorithms are developed in this paper, which are named finite-time and adaptive-gain DAT algorithms. Based on the finite-time one, the states of the physical agents in this paper can track the average of the time-varying reference signals within a finite settling time. Furthermore, the finite settling time is also estimated by considering a well-designed Lyapunov function in this paper. Compared with asymptotical DAT algorithms, the proposed finite-time algorithm not only solve finite-time DAT problems but also ensure states of physical agents to achieve an accurate average of the multiple signals. Then, an adaptive-gain DAT algorithm is designed. Based on the adaptive-gain one, the DAT problem is solved without global information. Thus, it is fully distributed. Finally, numerical simulations show the effectiveness of the theoretical results.

published proceedings

  • IEEE Trans Neural Netw Learn Syst

altmetric score

  • 0.25

author list (cited authors)

  • Zhao, Y. u., Liu, Y., Wen, G., & Huang, T.

citation count

  • 32

complete list of authors

  • Zhao, Yu||Liu, Yongfang||Wen, Guanghui||Huang, Tingwen

publication date

  • June 2019