针对执行器攻击的安全过滤器

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Cédric Escudero, Carlos Murguia, Daniel Quevedo, Paolo Massioni, Eric Zamaï
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引用次数: 0

摘要

本文的重点是减轻欺骗攻击对控制信号的影响,也就是说,在对手存在的情况下,篡改从控制器到系统执行器的数据,以降低工厂的性能。我们建议在环路中添加多输入多输出(MIMO)滤波器,在接收到的控制动作(可能被攻击破坏)和植物执行器之间。这些过滤器旨在动态地将攻击信号诱导的可达集引导到状态空间的已知安全区域。我们提供了一个综合框架(根据半确定程序集合的解决方案构建)来设计滤波器,使无攻击的控制信号尽可能少地失真-就H∞而言$$ {H}_{\infty } $$和h2 $$ {H}_2 $$原控制信号和滤波后控制信号之差的范数,并且轨迹保证包含在预定义的安全集中。最后以某型飞机增稳系统为例进行了仿真分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Safety Filters Against Actuator Attacks

Safety Filters Against Actuator Attacks

This manuscript focuses on mitigating the effect of deception attacks on control signals, that is, in the presence of an adversary that tampers with data coming from the controller to the system actuators in order to degrade the plant performance. We propose adding Multiple-Inputs Multiple-Outputs (MIMO) filters to the loop, between the received control actions (which are potentially corrupted by attacks) and the plant actuators. These filters are designed to dynamically steer the reachable set induced by the attack signals to a known safe region of the state space. We provide a synthesis framework (built in terms of the solution of a collection of semidefinite programs) to design the filters so that attack-free control signals are distorted as little as possible–in terms of H $$ {H}_{\infty } $$ and H 2 $$ {H}_2 $$ norms of the difference between original and filtered control signals–and the trajectories are guaranteed to be contained in a predefined safe set. The results are illustrated through a simulation case focusing on the stability augmentation system of an airplane.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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