Robust fixed-time synchronization of fuzzy shunting-inhibitory cellular neural networks with feedback and adaptive control

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-04-12 DOI:10.1002/acs.3808

Zhenjiang Liu, Yi-Fei Pu, Xiyao Hua, Xingxing You

引用次数: 0

Abstract

This article addresses the robust fixed-time synchronization of fuzzy shunting-inhibitory cellular neural networks (FSICNNs) with delays by utilizing two different types of control strategies. First, a feedback controller is proposed to achieve fixed-time synchronization of FSICNNs. Secondly, a novel adaptive controller is designed to guarantee fixed-time synchronization of FSICNNs, automatically adjusting all control gains without the need for advanced settings. The use of differential inequality techniques and the Lyapunov function method yields several sufficient conditions to ensure fixed-time synchronization for the considered FSICNNs. Finally, an example, along with its numerical simulation, is presented to demonstrate the validity of the proposed theoretical results.

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带反馈和自适应控制的模糊分流抑制蜂窝神经网络的鲁棒固定时间同步化

本文利用两种不同的控制策略，解决了有延迟的模糊分流抑制细胞神经网络（FSICNN）的稳健固定时间同步问题。首先，提出了一种反馈控制器来实现 FSICNN 的固定时间同步。其次，设计了一种新型自适应控制器来保证 FSICNN 的固定时间同步，无需高级设置即可自动调整所有控制增益。微分不等式技术和 Lyapunov 函数方法的使用产生了几个充分条件，以确保所考虑的 FSICNN 的定时同步。最后，介绍了一个实例及其数值模拟，以证明所提理论结果的正确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.