A novel adaptive neural predefined time control for a class of nonlinear systems

Abstract In this article, a novel adaptive neural predefined time control scheme is designed for a class of uncertain nonlinear systems. In the design procedure, the unknown smooth nonlinear functions are approximated by the neural networks (NNs). A neural adaptive predefined time controller is proposed based on NNs, adaptive backstepping technology, and predefined time stability theory. The designed control strategy includes a new adaptive updating law which ensures that the derivative of the Lyapunov function satisfies the predefined time stable form. The proposed control scheme ensures that all the signals in the closed‐loop system are predefined time stability. A practical simulation example validates the effectiveness of the designed controller.