Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems

In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use of predictive arguments with a twofold aim:1)Promptly detect malicious agent behaviors affecting normal system operations;2)Apply specific control actions,based on predictive ideas,for mitigating as much as possible undesirable domino effects resulting from adversary operations.Specifically,the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent.Finally,numerical simulations are carried out to show benefits and effectiveness of the proposed approach.     

A Resilient Control Strategy for Cyber-Physical Systems Subject to Denial of Service Attacks: A Leader-Follower Set-Theoretic Approach

Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency, reliability and sustainability. Although technologically cost-effective, this makes them vulnerable to cyber-attacks with potentially catastrophic consequences. To this end, we present a novel control architecture capable to deal with the distributed constrained regulation problem in the presence of time-delay attacks on the agents’ communication infrastructure. The basic idea consists of orchestrating the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed to isolate the attacked unit before it compromises the system operations. Simulations on a multi-area power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial of-service (DoS) attacks.      

Resilient and Safe Platooning Control of Connected Automated Vehicles Against Intermittent Denial-of-Service Attacks

Connected automated vehicles (CAVs) serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety, and reducing fuel consumption and vehicle emissions. A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads. This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service (DoS) attacks that disrupt vehicle-to-vehicle communications. First, a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties, including diverse vehicle masses and engine inertial delays, unknown and nonlinear resistance forces, and a dynamic platoon leader. Then, a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability, attack resilience, platoon safety and scalability. Furthermore, a numerically efficient offline design algorithm for determining the desired platoon control law is developed, under which the platoon resilience against DoS attacks can be maximized but the anticipated stability, safety and scalability requirements remain preserved. Finally, extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.      

Residual-Based False Data Injection Attacks Against Multi-Sensor Estimation Systems

This paper investigates the security issue of multisensor remote estimation systems. An optimal stealthy false data injection(FDI) attack scheme based on historical and current residuals, which only tampers with the measurement residuals of partial sensors due to limited attack resources, is proposed to maximally degrade system estimation performance. The attack stealthiness condition is given, and then the estimation error covariance in compromised state is derived to quantify the system perfor...     

Resilient iterative learning control for a class of discrete-time nonlinear systems under hybrid attacks

The security control problem for a class of unknown nonlinear systems is considered in this paper. For the nonlinear system running in the network environment, the measurement channel is subjected to hybrid attacks. Intermittent denial of service attacks and false data injection attacks are modeled as the hybrid attacks. According to the characteristics of the repetitive system, a resilient iterative learning control (ILC) algorithm under hybrid attacks is devised. Subsequently, the stability of the system is proved by mathematical derivation and theoretical analysis in the sense of mathematical expectation. The theoretical analysis results indicate that the resilient ILC algorithm can ensure the stability of the system, and the tracking error converges with the increased number of iterations. Finally, the validity of the algorithm is illustrated by numerical simulation and mobile robot simulation.     

一类时滞大系统的分散弹性控制器设计:自适应方法

研究了一类时滞大系统的分散弹性自适应控制器的设计问题.当控制器增益摄动范数有界但上界未知时,采用自适应方法,给出了系统一致有界稳定的条件和控制器的设计方案,且该控制器具有在线调整的功能.并给出了特例情况下,即控制器增益摄动范数有界且上界已知时,闭环系统可镇定的充分条件和相应弹性控制器的设计方案.数值算例说明了设计的可行性和有效性.     

线性时变大系统递阶控制的一种新方法

根据正交函数逼近理论，本文提出了解决时变大系统递阶控制的一种新型逼近算法。文中首先简单介绍了ＰＭＣＰ，同时给出了一些新的研究结果；研究了其在两点边值问题中的逼近解。动态大系统的逼近控制分为二级，第一级是子系统的优化问题，采用ＰＭＣＰ逼近技术解决；第二级为协调级，协调向量也通过ＰＭＣＰ逼近变换求解，这样使问题得到大为简化，不但算法简单，便于计算机运算，而且逼近精度高。数值仿真例子表明了本文提出的算法     

线性时变离散系统的稳定性

本文利用文[1]中的Gauss-Seidel迭代方法研究了线性时变离散系统的稳定性,得到了稳定性的若干代数判据。     

不确定离散时滞分段系统的广义H2弹性控制

针对一类不确定离散时滞分段系统,研究了广义H2稳定性分析和带有时滞的状态反馈弹性控制器设计问题.通过构造适当的离散分段二次李亚普诺夫函数,利用分段二次李亚普诺夫稳定性理论,给出了对于所有的容许参数不确定性,闭环系统是广义H2稳定的充分条件;在此基础上,基于线性矩阵不等式(LMI)处理方法,提出了带有时滞的状态反馈弹性控制器增益阵的设计方案.仿真实例验证了所提方法的有效性.     

一种新的时变系统极点配置自适应控制方法*

本文针对连续快时变系统，提出不要求系统参数未知部分上界的先验信息的自适应算法，得到间接自适应控制方案并且证明闭环系统稳定，仿真结果说明本文的方法有效．     

Passivity-Based Robust Control Against Quantified False Data Injection Attacks in Cyber-Physical Systems

Secure control against cyber attacks becomes increasingly significant in cyber-physical systems (CPSs). False data injection attacks are a class of cyber attack...     

基于MATLAB的时变系统自适应控制的仿真

本文介绍了基于MATLAB的仿真工具SIMUUNK．对于线性时变系统的模型参考自适应控制的仿真研究．并给出了仿真结果。     

时变系统的自适应跟踪控制*

本文将基于滑模变结构控制的模型偏差补偿控制方案，应用于一类线性时变系统的自适应控制，实现了高精度的连续轨迹跟踪，并且通过对典型时变对象－飞机的俯仰控制系统的仿真，证明了该方案在实际应用中的可行性。     

Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks

Cyber attacks pose severe threats on synchronization of multi-agent systems. Deception attack, as a typical type of cyber attack, can bypass the surveillance of the attack detection mechanism silently, resulting in a heavy loss. Therefore, the problem of mean-square bounded synchronization in multi-agent systems subject to deception attacks is investigated in this paper. The control signals can be replaced with false data from controller-to-actuator channels or the controller. The success of the attack is measured through a stochastic variable. A distributed impulsive controller using a pinning strategy is redesigned, which ensures that mean-square bounded synchronization is achieved in the presence of deception attacks. Some sufficient conditions are derived, in which upper bounds of the synchronization error are given. Finally, two numerical simulations with symmetric and asymmetric network topologies are given to illustrate the theoretical results.      

DoS攻击下网络控制系统的记忆型事件触发控制

针对一类网络化控制系统，当考虑网络控制系统遭受PWM （Pulsewidth-Modulated）型DoS （Denial-of-Service， DoS）攻击时，提出一种基于缓存机制的记忆型事件触发机制策略.本文考虑的DoS攻击可检测，并且攻击的周期时长以及每周期内的最短休眠时间已知.为了减少网络控制系统中数据包的发送频次，本文设计了基于相对误差的新型事件触发策略，与传统事件触发策略相比，通过增加缓存器来有效利用已经发送的历史采样数据，最终达到改善系统动态过程的目的.接下来，综合考虑网络攻击和事件触发方案，建立了网络化切换系统模型，构造分段李雅普诺夫泛函，推导出系统指数稳定的结论并且对控制器增益及事件触发参数进行协同设计.最后，通过仿真案例，验证了所提出方法的有效性.     

Exponential Stability of Slowly Time-Varying Nonlinear Systems

Let be a time-varying vector field depending on t containing a regular and a slow time scale (α large). Assume there exist a k (τ)≥1 and a γ(τ) such that ∥x _τ(t, t ₀, x ₀)∥≤k(τ) e ^{−γ(τ)(t−t0)}∥x ₀∥, with x _τ(t, t ₀, x ₀) the solution of the parametrized system with initial state x ₀ at t ₀. We show that for α sufficiently large is exponentially stable when “on average”γ(τ) is positive. The use of this result is illustrated by means of two examples. First, we extend the circle criterion. Second, exponential stability for a pendulum with a nonlinear slowly time-varying friction attaining positive and negative values is discussed. Date received: January 22, 2000. Date revised: April 14, 2001.     

DoS攻击下基于多率采样的多智能体系统安全一致性

本 文 研 究 了 一 类 带 有 多 率 采 样 的 线 性 多 智 能 体 系 统(Multiagent Systems, MASs)在 拒 绝 服务(Denial-of-Service, DoS)攻击下的安全一致性控制问题, 其中DoS攻击通常阻断智能体之间的信息传输. 本文将多率采样在网络化控制系统中的结果推广到了多智能体系统, 并考虑了非理想通信网络环境. 首先, 通过引入一个匹配机制来同步由多率采样引起的智能体不同状态分量的采样数据. 然后, 在DoS攻击下, 针对带有多率采样的线性MAS提出了一个基于多率采样的安全一致性控制器. 通过使用李雅普诺夫稳定性理论和切换系统方法, 获得了包含DoS 攻击持续时间以及攻击频率的安全一致性充分条件. 最后, 给出了一个仿真例子来验证所提方法的有效性, 并给出了多率采样与单率采样机制的性能对比分析.     

Sliding Mode Control for Nonlinear Markovian Jump Systems Under Denial-of-Service Attacks

This paper investigates the sliding mode control (SMC) problem for a class of discrete-time nonlinear networked Markovian jump systems (MJSs) in the presence of probabilistic denial-of-service (DoS) attacks. The communication network via which the data is propagated is unsafe and the malicious adversary can attack the system during state feedback. By considering random Denial-of-Service attacks, a new sliding mode variable is designed, which takes into account the distribution information of the probabilistic attacks. Then, by resorting to Lyapunov theory and stochastic analysis methods, sufficient conditions are established for the existence of the desired sliding mode controller, guaranteeing both reachability of the designed sliding surface and stability of the resulting sliding motion. Finally, a simulation example is given to demonstrate the effectiveness of the proposed sliding mode control algorithm.      

具有时变不确定性的脉冲时滞大系统的鲁棒稳定性

提出并研究了具有时变不确定性的脉冲时滞大系统的鲁棒稳定性,借助于向量比较原理和矩阵不等式等方法,对该系统建立了若干大范围指数鲁棒稳定的判据,并举例说明了结论的有效性。     

A Composite State Convergence Scheme for Bilateral Teleoperation Systems

State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master and slave systems. Second, it presents an elegant design procedure which requires a set of equations to be solved in order to compute the control gains of the bilateral loop. These design conditions are obtained by turning the master-slave error into an autonomous system and imposing the desired dynamic behavior of the teleoperation system. Resultantly, the convergence of master and slave states is achieved in a well-defined manner. The present study aims at achieving a similar convergence behavior offered by state convergence controller while reducing the number of variables sent across the communication channel. The proposal suggests transmitting composite master and slave variables instead of full master and slave states while keeping the operator’s force channel intact. We show that, with these composite and force variables; it is indeed possible to achieve the convergence of states in a desired way by strictly following the method of state convergence. The proposal leads to a reduced complexity state convergence algorithm which is termed as composite state convergence controller. In order to validate the proposed scheme in the absence and presence of communication time delays, MATLAB simulations and semi-real time experiments are performed on a single degree-of-freedom teleoperation system.