A Study of Potential Security and Safety Vulnerabilities in Cyber-Physical Systems

The work in this dissertation focuses on two examples of Cyber-Physical Systems (CPS), integrations of communication and monitoring capabilities to control a physical system, that operate in adversarial environments. That is to say, it is possible for individuals with malicious intent to gain access to various components of the CPS, disrupt normal operation, and induce harmful impacts. Such a deliberate action will be referred to as an attack. Therefore, some possible attacks against two CPSs will be studied in this dissertation and, when possible, solutions to handle such attacks will also be suggested. The first CPS of interest is vehicular platoons wherein it is possible for a number of partially-automated vehicles to drive autonomously towards a certain destination with as little human driver involvement as possible. Such technology will ultimately allow passengers to focus on other tasks, such as reading or watching a movie, rather than on driving. In this dissertation three possible attacks against such platoons are studied. The first is called ”the disbanding attack” wherein the attacker is capable of disrupting one platoon and also inducing collisions in another intact (non-attacked) platoon vehicles. To handle such an attack, two solutions are suggested: The first solution is formulated using Model Predictive Control (MPC) optimal technique, while the other uses a heuristic approach. The second attack is False-Data Injection (FDI) against the platooning vehicular sensors is analyzed using the reachability analysis. This analysis allows us to validate whether or not it is possible for FDI attacks to drive a platoon towards accidents. Finally, mitigation strategies are suggested to prevent an attacker-controlled vehicle, one which operates inside a platoon and drives unpredictably, from causing collisions. These strategies are based on sliding mode control technique and once engaged in the intact vehicles, collisions are reduced and eventual control of those vehicles will be switched from auto to human to further reduce the impacts of the attacker-controlled vehicle. The second CPS of interest in this dissertation is Heating, Ventilating, and Air Conditioning (HVAC) systems used in smart automated buildings to provide an acceptable indoor environment in terms of thermal comfort and air quality for the occupants For these systems, an MPC technique based controller is formulated in order to track a desired temperature in each zone of the building. Some previous studies indicate the possibility of an attacker to manipulate the measurements of temperature sensors, which are installed at different sections of the building, and thereby cause them to read below or above the real measured temperature. Given enough time, an attacker could monitor the system, understand how it works, and decide which sensor(s) to target. Eventually, the attacker may be able to deceive the controller, which uses the targeted sensor(s) readings and raises the temperature of one or multiple zones to undesirable levels, thereby causing discomfort for occupants in the building. In order to counter such attacks, Moving Target Defense (MTD) technique is utilized in order to constantly change the sensors sets used by the MPC controllers and, as a consequence, reduce the impacts of sensor attacks

Research on Information Flow Topology for Connected Autonomous Vehicles

Information flow topology plays a crucial role in connected autonomous vehicles (CAVs). It describes how CAVs communicate and exchange information with each other. It predominantly affects the platoon\u27s performance, including the convergence time, robustness, stability, and scalability. It also dramatically affects the controller design of CAVs. Therefore, studying information flow topology is necessary to ensure the platoon\u27s stability and improve its performance. Advanced sliding mode controllers and optimisation strategies for information flow topology are investigated in this project. Firstly, the impact of information flow topology on the platoon is studied regarding tracking ability, fuel economy and driving comfort. A Pareto optimal information flow topology offline searching approach is proposed using a non-dominated sorting genetic algorithm (NSGA-II) to improve the platoon\u27s overall performance while ensuring stability. Secondly, the concept of asymmetric control is introduced in the topological matrix. For a linear CAVs model with time delay, a sliding mode controller is designed to target the platoon\u27s tracking performance. Moreover, the Lyapunov analysis is used via Riccati inequality to guarantee the platoon\u27s internal stability and input-to-output string stability. Then NSGA-II is used to find the homogeneous Pareto optimal asymmetric degree to improve the platoon\u27s performance. A similar approach is designed for a nonlinear CAVs model to find the Pareto heterogeneous asymmetric degree and improve the platoon\u27s performance. Thirdly, switching topology is studied to better deal with the platoon\u27s communication problems. A two-step switching topology framework is introduced. In the first step, an offline Pareto optimal topology search with imperfect communication scenarios is applied. The platoon\u27s performance is optimised using a multi-objective evolutionary algorithm based on decomposition (MOEA/D). In the second step, the optimal topology is switched and selected from among the previously obtained Pareto optimal topology candidates in real-time to minimise the control cost. For a continuous nonlinear heterogeneous platoon with actuator faults, a sliding mode controller with an adaptive mechanism is developed. Then, the Lyapunov approach is applied to the platoon\u27s tracking error dynamics, ensuring the systems uniformly ultimately bounded stability and string stability. For a discrete nonlinear heterogeneous platoon with packet loss, a discrete sliding mode controller with a double power reaching law is designed, and a modified MOEA/D with two opposing adaptive mechanisms is applied in the two-step framework. Simulations verify all the proposed controllers and frameworks, and experiments also test some. The results show the proposed strategy\u27s effectiveness and superiority in optimising the platoon\u27s performance with multiple objectives

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

Distributed Model Reference Adaptive Control for Vehicle Platoons with Uncertain Dynamics

This paper proposes a distributed model reference adaptive controller (DMRAC) for vehicle platoons with constant spacing policy, subjected to uncertainty in control effectiveness and inertial time lag. It formulates the uncertain vehicle dynamics as a matched uncertainty, and is applicable for both directed and undirected topologies. The directed topology must contain at least one spanning tree with the leader as a root node, while the undirected topology must be static and connected with at least one follower receiving information from the leader. The proposed control structure consists of a reference model and a main control system. The reference model is a closed-loop system constructed from the nominal model of each follower vehicle and a reference control signal. The main control system consists of a nominal control signal based on cooperative state feedback and an adaptive term. The nominal control signal allows the followers cooperatively track the leader, while the adaptive term suppresses the effects of uncertainties. Stability analysis shows that global tracking errors with respect to the reference model and with respect to the leader are asymptotically stable. The states of all followers synchronize to both the reference and leader states. Moreover, with the existence of unknown external disturbances, the global tracking errors remain uniformly ultimately bounded. The performance of the controlled system is verified through the simulations and validates the efficacy of the proposed controller

Development of Robust Control Strategies for Autonomous Underwater Vehicles

The resources of the energy and chemical balance in the ocean sustain mankind in many ways. Therefore, ocean exploration is an essential task that is accomplished by deploying Underwater Vehicles. An Underwater Vehicle with autonomy feature for its navigation and control is called Autonomous Underwater Vehicle (AUV). Among the task handled by an AUV, accurately positioning itself at a desired position with respect to the reference objects is called set-point control. Similarly, tracking of the reference trajectory is also another important task. Battery recharging of AUV, positioning with respect to underwater structure, cable, seabed, tracking of reference trajectory with desired accuracy and speed to avoid collision with the guiding vehicle in the last phase of docking are some significant applications where an AUV needs to perform the above tasks. Parametric uncertainties in AUV dynamics and actuator torque limitation necessitate to design robust control algorithms to achieve motion control objectives in the face of uncertainties. Sliding Mode Controller (SMC), H / μ synthesis, model based PID group controllers are some of the robust controllers which have been applied to AUV. But SMC suffers from less efficient tuning of its switching gains due to model parameters and noisy estimated acceleration states appearing in its control law. In addition, demand of high control effort due to high frequency chattering is another drawback of SMC. Furthermore, real-time implementation of H / μ synthesis controller based on its stability study is restricted due to use of linearly approximated dynamic model of an AUV, which hinders achieving robustness. Moreover, model based PID group controllers suffer from implementation complexities and exhibit poor transient and steady-state performances under parametric uncertainties. On the other hand model free Linear PID (LPID) has inherent problem of narrow convergence region, i.e.it can not ensure convergence of large initial error to zero. Additionally, it suffers from integrator-wind-up and subsequent saturation of actuator during the occurrence of large initial error. But LPID controller has inherent capability to cope up with the uncertainties. In view of addressing the above said problem, this work proposes wind-up free Nonlinear PID with Bounded Integral (BI) and Bounded Derivative (BD) for set-point control and combination of continuous SMC with Nonlinear PID with BI and BD namely SM-N-PID with BI and BD for trajectory tracking. Nonlinear functions are used for all P,I and D controllers (for both of set-point and tracking control) in addition to use of nonlinear tan hyperbolic function in SMC(for tracking only) such that torque demand from the controller can be kept within a limit. A direct Lyapunov analysis is pursued to prove stable motion of AUV. The efficacies of the proposed controllers are compared with other two controllers namely PD and N-PID without BI and BD for set-point control and PD plus Feedforward Compensation (FC) and SM-NPID without BI and BD for tracking control. Multiple AUVs cooperatively performing a mission offers several advantages over a single AUV in a non-cooperative manner; such as reliability and increased work efficiency, etc. Bandwidth limitation in acoustic medium possess challenges in designing cooperative motion control algorithm for multiple AUVs owing to the necessity of communication of sensors and actuator signals among AUVs. In literature, undirected graph based approach is used for control design under communication constraints and thus it is not suitable for large number of AUVs participating in a cooperative motion plan. Formation control is a popular cooperative motion control paradigm. This thesis models the formation as a minimally persistent directed graph and proposes control schemes for maintaining the distance constraints during the course of motion of entire formation. For formation control each AUV uses Sliding Mode Nonlinear PID controller with Bounded Integrator and Bounded Derivative. Direct Lyapunov stability analysis in the framework of input-to-state stability ensures the stable motion of formation while maintaining the desired distance constraints among the AUVs

Distributed Model Reference Control for Cooperative Tracking of Vehicle Platoons Subjected to External Disturbances and Bounded Leader Input

This paper proposes a distributed model reference controller (DMRC) for cooperative tracking of vehicle platoons subjected to unknown external disturbances and bounded, non-zero leader input. The vehicle-to-vehicle communication network topology is assumed to be directed and contains at least one spanning tree with the leader as a root node. The proposed scheme utilizes the cooperative tracking error reference as a virtual reference for each follower. The main control system is designed using cooperative tracking error and cooperative disagreement error to attenuate the effects of unknown external disturbance and allow for bounded leader input. The global disagreement error is shown to be uniformly ultimately bounded through detailed stability analysis, such that the states of each follower synchronize to the leader states with bounded residual error, and guarantees input-to-state string stability (ISSS) of the platoon. Performance verification is conducted through simulations and validates the efficacy of DMRC for the vehicle platoon problem

A Comparative Study of Vehicle Platoon with Limited Output Information in Directed Topologies

This paper aims to study and compare the effect of limited-output information in various directed topology to the performance of vehicle platoon. Two distributed controllers based on limited-output information will be compared to cooperative state variable feedback control which designed based on full-state information. The comparison will be conducted for four common directed topologies in the vehicle platoon application. Simulation analysis is performed in three scenarios, namely under normal operations, when the leader moves with constant acceleration and when the platoon is subjected to constant communication delay. Performances comparison will be observed from inter-vehicular distance response in each follower and the results will be displayed with respect to the follower vehicle index in the platoon configuration. Finally, the behavior of each control scheme in various topologies will be summarized

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Leveraging Connected Highway Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting Under Moving Blocks

Future advanced Positive Train Control systems may allow North American railroads to introduce moving blocks with shorter train headways. This research examines how closely following trains respond to different throttle and brake inputs. Using insights from connected automobile and truck platooning technology, six different following train control algorithms were developed, analyzed for stability, and evaluated with simulated fleets of freight trains. While moving blocks require additional train spacing beyond minimum safe braking distance to account for train control actions, certain following train algorithms can help minimize this distance and balance fuel efficiency and train headway by changing control parameters