Improved Fixed-Time Stabilization of Fuzzy Neural Networks With Distributed Delay via Adaptive Sliding Mode Control
Fangmin Ren, Xiaoping Wang, Zhigang Zeng
Abstract
This article investigates fixed-time stabilization of fuzzy neural networks with distributed delay by designing an adaptive sliding mode controller. First, according to stability theory and related inequalities, a new fixed-time stability theorem is put forward, and the settling time is given. In order to stabilize the system, a new integral sliding mode surface is designed, and the corresponding sliding mode control strategy and adaptive sliding mode control strategy are established. Some criteria that can be obtained, and it is shown that the neuronal states of neural networks will arrive at the sliding surface in a fixed time, and then approach zero along the sliding surface. Compared with existing sliding mode control techniques, this work extends the previous related results by choosing different parameters of the controller and the sliding mode manifold to gain various protocols. Finally, two examples are provided to verify the validity of the theorems in this work.