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  4. Synchronization of time invariant uncertain delayed neural networks in finite time via improved sliding mode control

Synchronization of time invariant uncertain delayed neural networks in finite time via improved sliding mode control

MMC.
2021;
Volume 8, Number 2
: pp. 228–240
https://doi.org/10.23939/mmc2021.02.228
Received: February 24, 2021
Accepted: April 11, 2021

Mathematical Modeling and Computing, Vol. 8, No. 2, pp. 228–240 (2021)

Authors:
  1. N. Jayanthi
  2. R. Santhakumari
1
Government Arts College, Coimbatore, India
2
Government Arts College, Coimbatore, India; Sri Ramakrishna College of Arts and Science, Coimbatore, India

This paper explores the finite-time synchronization problem of delayed complex valued neural networks with time invariant uncertainty through improved integral sliding mode control.  Firstly, the master-slave complex valued neural networks are transformed into two real valued neural networks through the method of separating the complex valued neural networks into real and imaginary parts.  Also, the interval uncertainty terms of delayed complex valued neural networks are converted into the real uncertainty terms.  Secondly, a new integral sliding mode surface is designed by employing the master-slave concept and the synchronization error of master-slave systems such that the error system can converge to zero in finite-time along the constructed integral sliding mode surface.  Next, a suitable sliding mode control is designed by using Lyapunov stability theory such that state trajectories of the system can be driven onto the pre-set sliding mode surface in finite-time.  Finally, a numerical example is presented to illustrate the effectiveness of the theoretical results.

sliding mode control
sliding mode surface
time-invariant uncertainty
time delay
neural networks
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