This paper studies the problem of secure control of automated vehicles in a platoon-based driving pattern over a vehicular ad-hoc network (VANET) subject to various cyber attacks. The platoon under consideration is a convoy of a leader vehicle whose control input is unknown to its following vehicles and some follower vehicles with uncertain heterogeneous engine time constants, bounded disturbance and noise. First, a local estimator is developed for each follower vehicle so as to construct some confidence ellipsoidal estimation region always enclosing vehicular true state regardless of uncertain heterogenous engine time constants, bounded disturbance and noise. A convex optimization algorithm is proposed to find some optimal ellipsoidal sets and recursively solve out gain matrices of the local estimators. Then, a scalable control protocol employing the state estimates from its local and underlying neighboring estimators is designed to accomplish secure platooning control. Under the derived design technique, the resulting closed-loop platooning tracking errors are proven to remain in the vicinity of zero. Comparative studies are conducted to validate the efficacy of the proposed control method on achieving the satisfactory platooning performance by handling different attack strategies.

This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded (UBB) external disturbance and measurement noise. In order to improve the estimation reliability and performance in cases of poor data collection and potential communication interruption, a multi-sensor network configuration is presented to cooperatively measure the vehicular yaw rate, and further compute local state and fault estimates. Toward this aim, an augmented descriptor vehicle model is first established, where the unknown sensor fault is modeled as an auxiliary state of the system model. Then, a new distributed ellipsoidal set-membership estimation approach is developed so as to construct an optimized bounding ellipsoidal set which guarantees to contain the vehicle's true state and the sensor fault at each time step despite the existence of UBB disturbance and measurement noises. Furthermore, a convex optimization algorithm is put forward such that the gain matrix of each distributed estimator can be recursively obtained. Finally, simulation results are provided to validate the effectiveness of the proposed approach.

This article is concerned with the resilient tracking control of a networked control system under cyber attacks. The attacker is an active adversary whose aim is to severely degrade the tracking performance of the system by launching deception attacks on the sensor-to-controller communication channels and denial-of-service attacks on the controller-to-plant channels, respectively. First, a concept of resilient set-membership tracking control is presented, through which the system's true state is guaranteed to reside in a bounding ellipsoidal set of the reference state regardless of the existence of attacks and unknown-but-bounded (UBB) noises. Second, in the case that full information of the system's state is not implicitly trusted in the presence of attacks, a resilient set-membership estimation strategy is provided to secure the state estimates against the deception attacks. Furthermore, based on a recursive computation of a reference state ellipsoid and confidence state estimation ellipsoids, a convex optimization algorithm in terms of recursive linear matrix inequalities is proposed to obtain the gain parameters for both the desired resilient state estimator and the tracking controller. Finally, the effectiveness of the proposed method is illustrated through an Internet-based three-tank system.

This paper is concerned with the distributed attack detection and recovery in a vehicle platooning control system, wherein inter-vehicle information is propagated via a wireless communication network. An active adversary may launch malicious cyber attacks to compromise both sensor measurements and control command data due to the openness of the wireless communication. First, a distributed attack detection algorithm is developed to identify any of those attacks. The core of the algorithm lies in that each designed filter can provide two ellipsoidal sets: a state prediction set and a state estimation set. Whether a filter can detect the occurrence of such an attack is determined by the existence of intersection between these two sets. Second, two recovery mechanisms are put forward, through which the adversarial effects of cyber attacks can be mitigated in a timely manner. The recovery mechanisms depend on reliable modifications of the attacked signals required for the computation of the two ellipsoidal sets. Finally, simulation is provided to validate the effectiveness of the proposed method in both detection and recovery phases.

In this study, a novel output feedback model predictive control based on ellipsoidal set-membership state estimation is proposed for systems with unknown but bounded external disturbances. The set-membership state estimation is utilised to estimate the current system states for the optimisation of model predictive control such that the actual states are not required. Ellipsoidal set-membership estimation guarantees that the real system state lies in the ellipsoid originated from the estimated state. The control inputs computed by solving the optimisation problem recursively regulate the system state to converge to a domain containing the origin. All the quadratic matrix inequality conditions are conservatively approximated as linear matrix inequality conditions such that the optimisation problems can be solved by using semi-definite programming. System constraints are analysed over all the prediction horizon and transformed into linear matrix inequalities for the direct incorporation into the optimisation. Simulation examples demonstrate the effectiveness of the proposed approach.

This paper studies an attack detection problem for a networked leader-following multi-agent system subject to unknown-but-bounded system noises and quantization effects, where an adversary launches malicious cyber attacks on agents' measurement outputs aiming to distrust the leader-following consensus. An effective distributed attack detection algorithm is firstly developed for each follower such that the attack can be identified at the time of its occurrence. The core of the algorithm lies in a set-membership filtering approach from which each designed filter can provide an ellipsoidal state prediction set and an ellipsoidal state estimation set. Whether a filter can detect the occurrence of such an attack is then determined by the existence of intersection between these two sets. Furthermore, a convex optimization algorithm is established to solve out anticipated consensus protocol and two-step set-membership filter by resorting to some recursive linear matrix inequalities. Finally, an illustrative example is given to show the effectiveness of the proposed main results.

This paper is concerned with cyber attack detection in a networked control system. A novel cyber attack detection method, which consists of two steps: 1) a prediction step and 2) a measurement update step, is developed. An estimation ellipsoid set is calculated through updating the prediction ellipsoid set with the current sensor measurement data. Based on the intersection between these two ellipsoid sets, two criteria are provided to detect cyber attacks injecting malicious signals into physical components (i.e., sensors and actuators) or into a communication network through which information among physical components is transmitted. There exists a cyber attack on sensors or a network exchanging data between sensors and controllers if there is no intersection between the prediction set and the estimation set updated at the current time instant. Actuators or network transmitting data between controllers and actuators are under a cyber attack if the prediction set has no intersection with the estimation set updated at the previous time instant. Recursive algorithms for the calculation of the two ellipsoid sets and for the attack detection on physical components and the communication network are proposed. Simulation results for two types of cyber attacks, namely a replay attack and a bias injection attack, are provided to demonstrate the effectiveness of the proposed method.

This paper is concerned with cyber attack detection problem in a platoon-based vehicular networked control system. In such a system, the information among vehicles is transmitted through a shared wireless communication network and also each vehicle has access to its own information measured by local sensors. These kind of systems are highly vulnerable to cyber attacks and therefore, cyber-security issues need to be properly addressed to ensure the safety of the systems. Among various cyber-security aspects, reliable attack detection is of utmost importance as the ability to detect cyber attacks in a timely manner can reduce the damage to the systems. Therefore, we present a cyber attack detection algorithm that is capable of detecting attacks violating both measurements and control command data. This algorithm is based on an ellipsoidal set-membership filtering approach which consists of two sets: prediction ellipsoid set and an estimation ellipsoid set calculated through updating the prediction ellipsoid set with the measurement data. The detection method depends on the existence of intersection between these two sets computed by the filter. Simulation results for some possible cyber attacks are provided to demonstrate the effectiveness of the proposed method.

This paper is concerned with cyber-physical attack detection problem in networked control systems subject to limited communication bandwidth. This constraint arises when an attack detection system is located at a remote site and so the required signals, measurement output and control signals, need to be transmitted over a digital communication channel. Therefore, data before being sent to the remote site must be encoded and converted from analog signals to digital signals by using quantizer. A quantizer maps the amount of information from a continuous space to a finite set which is compatible with the limited communication bandwidth. Considering the quantized measurement output, a detection algorithm by means of a set-membership filtering approach will be proposed. The algorithm consists of a prediction ellipsoid set and an estimation ellipsoid set updated with the quantized measurement output. The detection method depends on the existence of intersection between two sets computed by the filter. Simulation results for some possible physical and cyber attacks are provided to demonstrate the effectiveness of the proposed method.

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.

The steer-by-wire (SbW) system, in which the conventional mechanical linkage between the steering wheel and the front wheel is removed, is capable of acting as an actuator for the active front steering system enhancing vehicle handling performance and safety. Several control strategies have been utilized to control the front wheel subsystem, which is the main part of the SbW system, and the steering response of SbW in the presence of system uncertainties and external disturbance has been improved; however, improvement of the controller transient response is not considered in most of these control strategies. In this paper a nonsingular fast terminal sliding mode (NFTSM) control method for the front wheel subsystem is first established. The NFTSM technique aims to provide a fast transient response for the front wheel tracking controller in the existence of system uncertainties and disturbance including the tire self-aligning torque, Coulomb friction torque and variation of road condition. Simulation results confirm that the proposed nonsingular fast terminal sliding mode controller not only has strong robustness against uncertainties but also improves the transient response of the tracking controller.

Vehicle stability control system has evolved significantly over the past three decades. Several control strategies have been implemented to enhance the vehicle stability control performance. However, most of these control strategies have not been focused on improving the transient response for vehicle yaw rate and sideslip angle tracking controller in the presence of uncertainties and disturbance. This paper is aimed at reviewing the proposed control algorithms based on their control objectives, different types of actuators required for the vehicle stability control system, advantages and disadvantages. According to this review, we derive that the advanced type of sliding mode control with non-singular fast terminal sliding surface has an ideal capacity to provide a fast transient response of yaw rate and sideslip tracking controllers under the presence of disturbances.