FDI 攻击和输入饱和状态下开关非线性系统的自适应模糊跟踪控制:灵活的瞬态性能方法

IF 11.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-10-01 DOI:10.1109/TCYB.2024.3463689
Guangdeng Zong;Hongzhen Xie;Dong Yang;Xudong Zhao;Yang Yi
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引用次数: 0

摘要

本研究针对开关非线性系统提出了一种自适应模糊跟踪控制策略,该策略能够有效解决虚假数据注入(FDI)攻击和输入饱和问题,同时实现灵活的规定性能控制以及结果系统的半全局均匀极限约束。与之前的工作相比,所提供的控制策略有两个显著的优点:1)它引入了一个新颖的固定时间预给定性能函数,有效地平衡了输入饱和与输出约束;2)通过在反步进过程中实施模糊逻辑系统逼近技术,成功地减轻了 FDI 攻击造成的不利影响。建立了一组开关模糊观测器来估计不可观测的状态,同时利用一阶微分滤波器来处理复杂性爆炸问题。最后,给出了质量弹簧阻尼器系统,以证实所开发的方法。
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Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems Under FDI Attacks and Input Saturation: A Flexible Transient Performance Approach
The present study proposes an adaptive fuzzy tracking control strategy for switched nonlinear systems, capable of effectively addressing false data injection (FDI) attacks and input saturation, while achieving flexible prescribed performance control as well as semi-global uniform ultimate boundness for the resultant system. Compared to the previous work, the provided control strategy exhibits two notable strengths: 1) it introduces a novel modified fixed-time pregiven performance function to effectively balance input saturation and output constraint and 2) the detrimental impacts resulting from FDI attacks are successfully mitigated by implementing the fuzzy logic systems approximation technique in the backstepping procedure. A set of switching fuzzy observers are established to estimate the unobservable states while a first-order differential filter is utilized to handle the complexity explosion problem. Finally, the mass-spring-damper system is given to substantiate the developed approach.
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来源期刊
IEEE Transactions on Cybernetics
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.
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