Observer-Based Periodic Event-Triggered Adaptive Fuzzy Control for Networked Nonlinear Systems

IF 10.5 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Cybernetics Pub Date : 2025-04-16 DOI:10.1109/TCYB.2025.3554702

Ning Zhao;Huiyan Zhang;Xuan Qiu;Ramesh K. Agarwal

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引用次数: 0

Abstract

This article addresses the periodic event-triggered adaptive output feedback control problem for networked system with unknown nonlinear dynamics. Based on the output-dependent periodic event-triggered mechanism (PETM), a nonlinear observer is designed to estimate system states, where the fuzzy-logic systems-based approximation method and adaptive technique are employed to approximate and compensate for uncertainties. To enhance resource utilization efficiency in communication channels, a new observer and parameter estimators-dependent parallel PETM is proposed to schedule intermittent packet transmission. Then, a digital controller is designed to reduce frequent control updating. By constructing novel piecewise Lyapunov functional, it is proven that the underlying system states, the observation error signals and parameter estimation signals are semiglobally uniformly ultimately bounded. In addition, the proposed control method is applied to solve the stabilization problem of networked interconnected systems. Finally, a numerical simulation is performed to show the efficiency of the developed control method.

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基于观测器的网络非线性系统周期性事件触发自适应模糊控制

研究了具有未知非线性动力学特性的网络系统的周期事件触发自适应输出反馈控制问题。基于输出相关的周期事件触发机制（PETM），设计了非线性观测器来估计系统状态，采用基于模糊逻辑系统的逼近方法和自适应技术来逼近和补偿系统的不确定性。为了提高通信信道的资源利用效率，提出了一种新的依赖于观测器和参数估计器的并行PETM算法来调度间歇分组传输。然后，设计了数字控制器，以减少频繁的控制更新。通过构造新的分段Lyapunov泛函，证明了系统底层状态、观测误差信号和参数估计信号是半全局一致最终有界的。此外，还将所提出的控制方法应用于解决网络化互联系统的镇定问题。最后，通过数值仿真验证了所提控制方法的有效性。

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

IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS

CiteScore

25.40

自引率

11.00%

发文量

1869

期刊介绍： The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.