混合攻击下随机MIMO非线性CPSs的事件触发自适应逆最优控制

Event-Triggered Adaptive Inverse Optimal Control for Stochastic MIMO Nonlinear CPSs under Hybrid Cyber-Attacks

摘要

本文针对混合网络攻击环境下的一类多输入多输出 (Multiple-Input Multiple-Output, MIMO) 随机非线性信息物理系统 (Cyber-Physical Systems, CPSs)，研究其事件触发自适应逆最优控制问题。拒绝服务攻击 (Denial-of-Service, DoS) 和欺骗攻击 (False Data Injection, FDI) 组成的混合网络攻击模型采用概率伯努利模型，贴近真实攻击模型。在 Backstepping 方法的基础上，通过结合逆最优设计和切换阈值的事件触发机制，本文提出了一种事件触发自适应最优控制策略。该控制策略适用于随机 MIMO 系统，保证闭环系统在概率意义下半全局一致最终有界。仿真结果验证了所提策略的有效性和可行性。

Abstract

This paper investigates the event-triggered adaptive inverse optimal control problem for a class of stochastic multiple-input multiple-output (MIMO) nonlinear cyber-physical systems (CPSs) under hybrid cyber-attacks. The hybrid cyber-attack model, consisting of denial-of-service (DoS) and false data injection (FDI) attacks, is characterized by a probabilistic Bernoulli process to better capture realistic attack scenarios. Based on the backstepping approach, an event-triggered adaptive optimal control scheme is developed by integrating inverse optimal design with a switching-threshold event-triggered mechanism. The proposed method is applicable to stochastic MIMO systems and ensures that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB) in probability. Finally, simulation results are presented to demonstrate the effectiveness and feasibility of the proposed strategy.

关键词

随机非线性 CPSs / 混合网络攻击 / 事件触发 / 逆最优控制 / MIMO

Key words

stochastic nonlinear CPSs / hybrid cyber-attack / event-triggered / inverse optimal control / MIMO

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基金资助

国家自然科学基金(71871135)

广东省可再生能源重点实验室项目(E539kf0601)