Observer‐based attack‐resilient control for linear systems against FDI attacks on communication links from controller to actuators

For the adversarial attacks on the communication links from the controller to the actuators, most of the existing attack‐resilient control results focus on denial‐of‐service attacks. Unlike the existing results, this paper studies the observer‐based attack‐resilient control problem for linear systems with false data injection attacks and process disturbances. Due to limited resources, the malicious attacker is assumed to only manipulate a certain number of communication links from the controller to the actuators. A novel control architecture is proposed, which consists of an attack‐resilient state observer, a controller gain scheme, and a supervisory switching strategy. The observer is developed based on the maximin strategy, and state estimation will be used to construct the controller. The switching strategy is designed to pick an appropriate controller gain and prevent the attack signals from entering the plant automatically. It is shown that the closed‐loop system is stable with an attack‐resilient performance. Finally, to verify the effectiveness of the proposed controller, simulation results on a linearized reduced‐order aircraft system and an IEEE six‐bus power system are provided.     

FDI攻击下互联电力系统的分布式安全状态估计

针对虚假数据注入(FDI)攻击下的多区域互联电力系统安全状态估计问题,提出一种分布式中间观测器,同时对各区域电力系统的状态、虚假数据注入攻击信号以及负载偏差进行估计.首先,通过将电力系统的状态和虚假数据注入攻击进行增广,得到等价的区域电力系统状态空间模型;然后,基于等价系统模型构建分布式中间观测器,对各个电力子系统分别进行安全状态估计,并设计补偿控制策略以降低虚假数据注入攻击及负载偏差带来的影响;最后,通过算例仿真验证所提出方法的可行性和有效性.     

Extended observer-based hybrid tracking control strategy for networked system with FDI attacks

This paper studies the speed tracking control of networked control systems (NCSs) with external disturbance and false data injection (FDI) attacks. First, the system model with external disturbances and FDI attacks is built. Then, an extended observer based on discrete time sliding function and neural network (NN) is proposed to observe the extended states and suppress the effect of external disturbance and FDI attacks. Furthermore, a novel hybrid discrete-time sliding mode control (HDSMC) strategy combining discrete time sliding mode control with super-twisting control is designed to perform closed-loop control of the system, in which the exponential term and nonlinear term are constructed to restrain the jitters. The convergence and reachability of the sliding motion are proofed. Finally, the validity and feasibility of the proposed methods are proved by simulations and experiments.     

High-order sliding mode observers and integral backstepping sensorless control of IPMS motor

This paper presents a robust high-order sliding mode interconnected observer and an integral backstepping controller for a sensorless interior permanent magnet synchronous motor. To limit the chattering phenomenon on the observed state, a super twisting algorithm is combined with an interconnected observer to design a new high-order sliding mode observer which will be used for multiple-input multiple-output systems. The proposed observer is used to estimate in finite time the rotor position, the speed and the stator resistance. Moreover, a robust nonlinear controller based on the backstepping algorithm is designed where integral actions are introduced step by step. This controller allows to track a desired reference which is computed by using a maximum-torque-per-ampere strategy. Simulation results are shown to illustrate the performance of the proposed scheme by using significant trajectories including the zero speed and under parametric uncertainties.     

虚假数据注入攻击信号的融合估计

研究了信息物理系统中假数据注入(False data injection, FDI)攻击信号的检测问题. 在分布式融合框架下, 首先将FDI攻击信号建模为信息物理系统模型中的未知输入, 从而使得攻击信号的检测问题转化为对FDI攻击信号的实时估计问题. 其次, 在每个传感器端设计基于自适应卡尔曼滤波的FDI攻击信号的局部估计器; 在融合中心端引入补偿因子, 设计分布式信息融合准则以导出攻击信号的融合估计器. 特别地, 当FDI攻击信号是时变情况时, 融合过程中补偿因子的引入可以大大提高对攻击信号的估计精度. 最后, 通过两个仿真算例验证所提算法的有效性.     

感应电机高阶终端滑模磁链观测器的研究

提出了基于高阶非奇异终端滑模的感应电机转子磁链观测方法,用于实现感应电机的按转子磁链定向控制. 设计了非奇异终端滑模面及观测器的控制策略,利用所设计的控制策略推导出电机转子磁链信息. 为了抑制常规滑模存在的抖振现象,设计了定子电流观测器的高阶滑模控制律,可将控制信号直接用于电机转子磁链的估计. 较常规滑模观测器,所提方法具有较高的观测精度,并对电机参数变化具有良好的鲁棒性.仿真结果验证了方法的有效性.     

非线性不确定系统的鲁棒滑模观测器设计

对非线性不确定性系统,提出一种鲁棒滑模观测器.所提出的鲁棒滑模观测器通过滑模与相应的控制策略来实现,设计参数的选取不需要求解大量方程,同时能保证对系统的非线性不确定项具有鲁棒性.通过设计滑模,可以调整观测器跟踪系统状态的收敛速度,使状态估计达到预期的指标.仿真结果验证了提出方法的有效性.     

级联式滑模观测器的永磁同步电机鲁棒滑模控制

提出了一种基于无速度传感器运行的永磁同步电机非线性控制方法。针对电机速度和位置观测,设计了一种新颖的级联式滑模观测器,解决了传统滑模观测采用低通滤波器的相位延迟问题。前级电流滑模观测器得到反电动势,后级反电动势滑模观测器获取转速和位置信息,利用李亚普诺夫理论进行了稳定性分析。针对速度控制,提出了带扩张状态观测器的滑模速度控制器取代PI调节器,提高了系统的鲁棒性。在滑模观测和控制中均利用双曲正切函数取代符号函数,削弱了系统抖振。将上述方法应用到永磁同步电机矢量控制系统中,通过仿真验证方法的有效性。     

基于高阶滑模观测器的自适应时变滑模再入姿态控制

针对再入飞行器鲁棒姿态控制问题, 提出一种基于高阶滑模观测器的自适应时变滑模控制器设计方法. 首先, 设计了一种时变滑模面, 并在此基础上推导了相应的时变滑模控制律, 其中滑模控制中切换增益通过一种自适应算法获得, 消除了控制器设计过程中对系统不确定性上界已知的要求; 然后, 利用高阶滑模观测器对控制器设计过程中用到的姿态角导数信息进行观测, 同时能够获得系统扰动估计值, 从而构造一种基于观测器的控制器形式; 最后, 通过仿真验证了所提出的控制算法在提高再入飞行器姿态控制精度以及系统鲁棒性方面的有效性.     

Secure state estimation for cyber-physical systems with unknown input sliding mode observer

In recent years, cyber attacks have posed great challenges to the development of cyber-physical systems. It is of great significance to study secure state estimation methods to ensure the safe and stable operation of the system. This paper proposes a secure state estimation for multi-input and multi-output continuous-time linear cyber-physical systems with sparse actuator and sensor attacks. First, for sparse sensor attacks, we propose an adaptive switching mechanism to mitigate the impact of sparse sensor attacks by filtering out their attack modes. Second, an unknown input sliding mode observer is designed to not only observe the system states, sensor attack signals, and measurement noise present in the system but also counteract the effects of sparse actuator attacks through an unknown input matrix. Finally, for the design of an unknown input sliding mode state observer, the feasibility of the observing system is demonstrated by means of Lyapunov functions. Additionally, simulation experiments are conducted to show the effectiveness of this method.     

Fixed-time sliding mode observer-based controller for a class of uncertain nonlinear double integrator systems

This paper investigates a fixed-time convergence issue using the sliding mode observer-based controller for a class of uncertain nonlinear double integrator systems. This observer-based controller is designed assuming that only the first state measurement is available and there is no information about external disturbances and modeling uncertainties. A new form of sliding mode observer in combination with a sliding mode controller is designed to estimate unmeasured state and unknown disturbances and uncertainties as well as provide the estimated data in the control law. A novel form of sliding surfaces for the robust observer-based controller is proposed for which fixed-time convergence is guaranteed to achieve trajectory tracking. In the proposed fixed-time scheme, the bound on the settling time is user-defined using design parameters regardless of the system's initial conditions. The control law and observer law are designed such that the chattering issue is alleviated in the control signal. The stability analysis of the closed-loop system using the observer-based controller is established via the Lyapunov theory. The validity of the controller design is tested by applying and simulating an example of a robot manipulator in Simulink/MATLAB. The superiority of the proposed method is demonstrated by comparing it with two other methods from the relevant literature.     

The detection mechanism for false data injection attack via the ellipsoidal set-membership approach

The false data injection (FDI) attack detection problem in cyber-physical systems (CPSs) is investigated in this paper. A novel attack detection algorithm is proposed based on the ellipsoidal set-membership approach. In comparison to the existing FDI attack detection methods, the developed attack detection approach in this paper neither requires predefined thresholds nor specific statistical characteristics of the attacks. In order to guarantee that the estimation ellipsoid contains normal states despite the unknown but bounded (UBB) process and measurement noises, the one-step ellipsoidal set-membership estimation method is put forward. In addition, a convex optimization algorithm is introduced to calculate the gain matrix of the observer recursively. Moreover, with the help of the state estimation ellipsoid, the residual ellipsoid can be obtained for attack detection. Whether a detector can detect the FDI attack depends on the relationship between the residual value and residual ellipsoidal set. Finally, the effectiveness of the proposed method is demonstrated by a numerical simulation example.     

混合攻击下直流微电网的FDI估计与模糊控制联合设计

研究基于T-S模糊模型的直流微电网(DC-MG)系统在拒绝服务(DoS)和虚假数据注入(FDI)混合攻击下的协同估计控制框架.考虑网络化T-S模糊模型和并行分布补偿(PDC)模糊控制规则中的非均匀时间尺度,建立DC-MG系统的T-S模型.为了放宽现有的DoS攻击模型通常假定攻击的频率和持续时间均有限的要求,在攻击信号的休眠和活跃期的已知范围内提出一种新的DoS攻击模型.同时,构造一个切换脉冲观测器来估计由外部动态系统产生的未知FDI攻击信号.然后,利用依赖于攻击参数的时变Lyapunov函数方法,导出系统在混合攻击下的指数稳定性判据.此外,基于线性矩阵不等式给出了模糊控制器和FDI攻击观测器的联合设计方法.最后,通过案例研究验证了所提出理论结果的有效性.     

A robust fault diagnosis and accommodation scheme for robot manipulators

This paper investigates an algorithm for robust fault diagnosis (FD) in uncertain robotic systems by using a neural sliding mode (NSM) based observer strategy. A step by step design procedure will be discussed to determine the accuracy of fault estimation. First, an uncertainty observer is designed to estimate the uncertainties based on a first neural network (NN1). Then, based on the estimated uncertainties, a fault diagnosis scheme will be designed by using a NSM observer which consists of both a second neural network (NN2) and a second order sliding mode (SOSM), connected serially. This type of observer scheme can reduce the chattering of sliding mode (SM) and guarantee finite time convergence of the neural network (NN). The obtained fault estimations are used for fault isolation as well as fault accommodation to self-correct the failure systems. The computer simulation results for a PUMA560 robot are shown to verify the effectiveness of the proposed strategy.     

基于观测器的滑模控制非线性中立型时滞系统

针对一类状态不可测的非线性不确定中立型时滞系统,基于滑模控制理论,采用线性矩阵不等式的处理方法,提出了滑动模态鲁棒渐近稳定时滞相关的充分条件,设计了一类滑模观测器,同时给出了该观测器存在的充分条件;然后应用滑模控制的趋近率方法和基于观测器所得到的系统估计状态,综合了一类滑模控制器,该控制器同时保证了估计状态下滑模面和估计误差状态下滑模面的渐近可达性;最后通过数值实例证明了该控制方案的可行性.     

基于嵌套自适应观测器的 连铸结晶器振动位移系统有限时间容错控制

针对连铸结晶器振动位移系统存在伺服电机驱动单元等执行器故障和负载转矩扰动问题, 本文提出一种基于嵌套自适应观测器的有限时间容错策略. 首先, 设计一种嵌套自适应观测器在线估计由执行器故障和负载转矩扰动构成的综合不确定项; 其次, 采用分层设计与终端滑模相结合的方法, 分别对位移子系统和电流环子系统设计全阶滑模控制器(FOSMC)和终端滑模控制器补偿综合不确定项, 并通过引入一阶低通滤波器来提高控制信号的连续性. 理论分析表明, 本文所提容错控制策略能够保证闭环系统所有状态有限时间稳定; 最后, 通过仿真对比研究验证了本文所提控制策略的有效性.     

虚假数据注入攻击下直流微电网的滑模控制

针对一类控制通讯信道受到攻击下直流微电网系统母线电压波动问题,提出一种基于滑模控制方法的镇定策略,以实现动态控制与快速响应.首先,在直流微电网系统中引入蓄电池储能系统并构建系统数学模型;其次,设计积分滑模控制策略,控制储能系统注入镇定电流以稳定直流母线电压,从而抑制非线性扰动和虚假数据注入攻击对系统性能的影响;然后,借助适当的Lyapunov泛函,得到确保滑动模态渐近稳定和滑模面可达性的充分条件,保证直流微电网系统能够实现对负载需求的迅速响应及稳定运行;最后,通过Matlab数值仿真验证所提出的滑模控制策略的有效性.     

An adaptive unscented Kalman filter approach to secure state estimation for wireless sensor networks

Wireless sensor networks are vulnerable to false data injection attacks, which may mislead the state estimation. To solve this problem, this paper presents a chi-square test-based adaptive secure state estimation (CTASSE) algorithm for state estimation and attack detection. Taking advantage of Kalman filters, attack signal together with process noise or measurement noise are described as total white Gaussian noise with uncertain covariance matrix. The chi-square test method is used in the adaptation of the total noise covariance and attack detection. Then, a standard adaptive unscented Kalman filter (UKF) is used for the state estimation. Finally, simulation results show that the proposed CTASSE algorithm performs better than other UKFs in state estimation and is also effective in real-time attack detection.     

Fuzzy Sliding Mode Control for Active Suspension System with Proportional Differential Sliding Mode Observer

In this paper, a generalized augmented transformation is considered for the quarter active suspension system with uncertainties. Specifically, the model uncertainties are converted to the augmented states and a new proportion differential sliding mode observer is used to estimate state variables and model uncertainties. A differential geometric method is applied to linearize the nonlinear suspension model. In order to weaken the vibration effect of sliding mode control force and reduce energy consumption, a fuzzy sliding mode controller is designed for the active suspension system and the fuzzy controller is applied to adjust switching control gain according to the reaching condition of sliding mode surface. The simulations are conducted to illustrate the effectiveness and advantages of this proposed observer and control strategy.     

Robust control for a class of time-delay uncertain nonlinear systems based on sliding mode observer

In this paper, a robust control scheme is proposed for a class of time-delay uncertain nonlinear systems with unknown input using the sliding mode observer. The sliding mode state observer is given with radial basis function neural networks, and then the robust control scheme is presented based on the designed sliding mode observer. The developed observer-based control scheme consists of two parts. One term is a linear controller and the other term is a neural network controller. Using the Lyapunov method, a criterion for bounded stability of the closed-loop system is developed in terms of linear matrix inequalities. Finally, a simulation example is used to illustrate the effectiveness of the proposed robust control scheme.