Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.

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.

Resilient Time-Varying Formation-Tracking of Multi-UAV Systems Against Composite Attacks: A Two-Layered Framework

This paper studies the countermeasure design problems of distributed resilient time-varying formation-tracking control for multi-UAV systems with single-way communications against composite attacks,including denial-of-services(DoS)attacks,false-data injection attacks,camouflage attacks,and actuation attacks(AAs).Inspired by the concept of digital twin,a new two-layered protocol equipped with a safe and private twin layer(TL)is proposed,which decouples the above problems into the defense scheme against DoS attacks on the TL and the defense scheme against AAs on the cyber-physical layer.First,a topologyrepairing strategy against frequency-constrained DoS attacks is implemented via a Zeno-free event-triggered estimation scheme,which saves communication resources considerably.The upper bound of the reaction time needed to launch the repaired topology after the occurrence of DoS attacks is calculated.Second,a decentralized adaptive and chattering-relief controller against potentially unbounded AAs is designed.Moreover,this novel adaptive controller can achieve uniformly ultimately bounded convergence,whose error bound can be given explicitly.The practicability and validity of this new two-layered protocol are shown via a simulation example and a UAV swarm experiment equipped with both Ultra-WideBand and WiFi communication channels.

Attack-resilient control for converter-based DC microgrids

In light of the growing integration of renewable energy sources in power systems,the adoption of DC microgrids has become increasingly popular,due to its simple structure,having no frequency,power factor concerns.However,the dependence of DC microgrids on cyber-networks also makes them susceptible to cyber-attacks.Potential cyberattacks can disrupt power system facilities and result in significant economic and loss of life.To address this concern,this paper presents an attack-resilient control strategy for microgrids to ensure voltage regulation and power sharing with stable operation under cyber-attack on the actuators.This paper first formulates the cyber-security problem considering a distributed generation based microgrid using the converter model,after which an attack-resilient control is proposed to eliminate the actuator attack impact on the system.Steady state analysis and root locus validation illustrate the feasibility of the proposed method.The effectiveness of the proposed control scheme is demonstrated through simulation results.

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 costeffective,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 ofservice(DoS)attacks.

Resilient predictive control for a class of uncertain time-delay systems

In practice, gain perturbations of controllers which axe caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.

Finite-Time Fuzzy Adaptive Output Feedback Resilient Control of Nonlinear Cyber-Physical Systems with Sensor Attacks and Actuator Faults

This paper studies the finite-time fuzzy adaptive output feedback resilient control problem for nonlinear cyber-physical systems(CPSs) with sensor attacks and actuator faults.Fuzzy logic systems(FLSs) are used to approximate the unknown nonlinear functions,and a fuzzy state observer is constructed to estimate the unmeasured states.By combining the Nussbaum function with the backstepping control design technique,a fuzzy adaptive resilient control scheme is designed to successfully address the effects of sensor attacks and actuator faults.It is proved that the controlled system is semi-global practical finite-time stability(SGPFS),and the tracking error converges to a small neighborhood of the origin in a finite time interval.Finally,the simulation and comparison results further demonstrate the effectiveness of the designed control method.

Distributed Detection Mechanism and Resilient Consensus Strategy for Secure Voltage Control of AC Microgrids

Distributed secondary control,depending on the sparse communication topology,excels for its flexibility and expandability in microgrids.The communication network plays an important role in microgrid control,but it is vulnerable to cyber-attacks.In this paper,the mathematical model for false data injection(FDI)attacks in AC microgrids is established,and the corresponding detection mechanism based on the morphological gradient is designed for the location of cyber-attacks in communication topology.Then,we propose a median-based resilient consensus voltage control strategy to mitigate the negative effects caused by malicious cyber-attacks and ensure the safe operation of the microgrid.Combining the detection method and resilient consensus control,a novel eventdriven mitigation scheme is derived to improve the resilience of microgrids under cyber-attacks.Finally,a tested microgrid model composed of five different distributed generation(DG)units is simulated in the MATLAB/Simulink environment.The feasibility and effectiveness of the presented detection mechanism and resilient consensus strategy are verified by simulation results applying different scenarios.

Observer‑Based Resilient Control of CACC Vehicle Platoon Against DoS Attack

Cooperative adaptive cruise control(CACC)is an important technology for improving road utilization and energy efficiency in the automotive industry.In CACC systems,connected vehicles can receive information from adjacent ones through com-munication networks.However,the networks are vulnerable to cyber-attacks,so the states of vehicles cannot be received promptly and accurately.This paper studies the security resilience control for a CACC system subject to denial of service(DoS)attack.The core of the proposed resilient control strategy is to estimate the delay caused by DoS attack and then compensate for it in the controller.Specifically,a CACC system is modeled by considering the impacts of DoS attack on the transmitted data.Then,a high-gain observer is presented to estimate the vehicle states including the time delay.The conver-gence of the observer is proved in a theorem based on the Lyapunov stability theory,and the high-gain-velocity observer is modified so that the estimation error of the velocity can converge to zero in a finite time.A resilient controller is designed by proposing a time delay compensation algorithm to mitigate the impacts of DoS attack.The effectiveness of the estimation and control methods is illustrated by a ten-vehicle simulation system operating at the FTP75 driving cycle conditions.And the relative estimation errors are less than 6%.

Direct adaptive actuator failure compensation control:a tutorial

A resilient control system is expected to have the capacity to restore the desired system stability and tracking performance in the presence of uncertain system faults such as actuator failures.While redundant actuators are used for actuator failure accommodation,uncertain actuator failures,whose failure time,pattern,and values may be unknown,can bring new challenges to feedback control design as such uncertain failures can introduce large structural,parametric,and actuation uncertainties.Two technical issues are associated with using redundant actuators:how redundant actuators should be coordinated for effective failure compensation control,and how a feedback control law should be adaptively designed to compensate uncertain actuator failures.In this paper,we present a tutorial on direct adaptive failure compensation-based solutions to these issues for different types of control systems:state tracking using state feedback,output tracking using state feedback or output feedback,for linear,non-linear,and multi-input multi-output systems.We give an overview on such adaptive actuator failure compensation designs which have special capacities to effectively use actuation redundancy to handle uncertain actuator failures,using either direct or indirect adaptive control approaches for direct adaptive actuator failure compensation without explicit failure detection,for fast and effective failure accommodation.

Resilient Control for Networked Control Systems Subject to Cyber/Physical Attacks

In this paper, we investigate a resilient control strategy for networked control systems（NCSs） subject to zero dynamic attacks which are stealthy false-data injection attacks that are designed so that they cannot be detected based on control input and measurement data. Cyber resilience represents the ability of systems or network architectures to continue providing their intended behavior during attack and recovery. When a cyber attack on the control signal of a networked control system is computed to remain undetectable from passive model-based fault detection and isolation schemes, we show that the consequence of a zero dynamic attack on the state variable of the plant is undetectable during attack but it becomes apparent after the end of the attack. A resilient linear quadratic Gaussian controller, having the ability to quickly recover the nominal behavior of the closed-loop system after the attack end, is designed by updating online the Kalman filter from information given by an active version of the generalized likelihood ratio detector.

Attack-resilient Distributed Control for Islanded Single-/three-phase Microgrids Based on Distributed Adaptive Observers

This paper investigates the power sharing and voltage regulation issues of islanded single-/three-phase microgrids(S/T-MGs)where both sources and loads are unbalanced and the presence of adversarial cyber-attacks against sensors of distributed generator(DG)units is considered.Firstly,each DG unit is modeled as a heterogeneous linear dynamic agent with disturbances caused by sources and loads,then the problem is formulated as a distributed containment control problem.After that,to guarantee satisfactory power sharing and voltage control performance asymptotically achieved for the S/T-MGs,an attack-resilient distributed secondary control approach is developed by designing a distributed adaptive observer.With this approach,the effect of the cyber-attacks can be neutralized to ensure system stability and preserve bounded voltage synchronization.Simulation results are presented to demonstrate the effectiveness of the proposed control approach.