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ISSN:2164-6457 (print)
ISSN:2164-6473 (online)
Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu

Complete Controllability of Nonlinear Neural Network Control Systems

Journal of Applied Nonlinear Dynamics 13(3) (2024) 583--590 | DOI:10.5890/JAND.2024.09.013

Amarnath Chaurasia, Santosh Kumar Tripathi, Anurag Shukla, Swati Maurya

Rajkiya Engineering College, Kannauj, Uttar Pradesh-209732, India

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Abstract

In this paper complete controllability of nonlinear neural control network systems is discussed. Using suitable substitution assumed system is converted in the first-order nonlinear differential equation with a nonzero linear part. With the use of controllability Grammian matrix, Lipschitz type nonlinearity, and fixed point theorem, some sufficient conditions for the complete controllability are derived. In the end, one numerical example and one LR (inductance and resistance) circuit example are discussed to validate the theoretical results.

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