Neural Computing and Applications

, Volume 22, Issue 1, pp 103–110

Guaranteed cost synchronous control of time-varying delay cellular neural networks

Authors

    • College of Science, Naval University of Engineering
  • Hanlin He
    • College of Science, Naval University of Engineering
  • Ping Xiong
    • College of Science, Naval University of Engineering
Original Article

DOI: 10.1007/s00521-011-0667-6

Cite this article as:
Tu, J., He, H. & Xiong, P. Neural Comput & Applic (2013) 22: 103. doi:10.1007/s00521-011-0667-6

Abstract

This paper deals with the synchronization of time-varying delay cellular neural networks. Based on the Lyapunov stability analysis and the zoned discussion and maximax synthesis (ZDMS) method, the quadratic matrix inequality (QMI) criterion for the guaranteed cost synchronous controller is designed to synchronize the given chaotic systems. For the convenience to solve, using a generalized result of Schur complement, the criterion in the form of QMI is turned into the linear matrix inequality (LMI) form, which can be used efficiently via existing numerical convex optimization algorithms such as the interior-point algorithms for solving LMIs. The minimization of the guaranteed cost is further studied, and the corresponding LMI criterion for getting the controller is given. Finally, numerical examples are given to show the effectiveness of proposed guaranteed cost synchronous control and its corresponding minimization problem.

Keywords

Synchronous controlGuaranteed cost controlSaturationTime-varying delayCellular neural network

Copyright information

© Springer-Verlag London Limited 2011