Complete Controllability of Nonlinear Neural Network Control Systems - Chaurasia, Amarnath; Tripathi, Santosh Kumar; Shukla, Anurag; Maurya, Swati (Journal of Applied Nonlinear Dynamics, 2026)
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.