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A networked control system (NCS) is a control system where sensors, actuators, and controllers are interconnected over a communication network. This dissertation presents a framework for modeling, stability analysis, optimal control, and bandwidth allocation of the NCS. A ball magnetic-levitation (maglev) system, four DC motor speed-control systems, and a wireless autonomous robotic wheelchair are employed as test beds to illustrate and verify the theoretical results of this dissertation. This dissertation first proposes an output feedback method to stabilize and control the NCSs. The random time delays in the controller-to-actuator and sensor-to-controller links are modeled with two time-homogeneous Markov chains while the packet losses are treated with Dirac delta functions. An asymptotic mean-square stability criterion is established to compensate for the network-induced random time delays and packet losses in the NCS. Then, an algorithm to implement the asymptotic mean-square stability criterion is presented. Experimental results illustrate effectiveness of the proposed output feedback method compared to conventional controllers. The proposed output feedback controller could reduce the errors of the NCS by 13% and 30–40% for the cases without and with data packet losses, respectively. The optimal bandwidth allocation and scheduling of the NCS with nonlinear-programming techniques is also presented in the dissertation. The bandwidth utilization (BU) of each client is defined in terms of its sampling frequency. Two nonlinear approximations, exponential and quadratic approximations, are formulated to describe the system performance governed by discrete-time integral absolute error (DIAE) versus sampling frequency. The optimal sampling frequencies are obtained by solving the approximations with Karush-Kuhn-Tucker (KKT) conditions. Simulation and experimental results are given to verify the effectiveness of the proposed approximations and the bandwidth allocation and scheduling algorithms. In simulations and experiments, the two approximations could maximize the total BU of the NCS up to about 98% of the total available network bandwidth.

This thesis is concerned with the analysis of the control design to the nonlinear networked control systems (NCSs). Ignoring the network connection and cascading actuators, the plant and sensors together, a sampled-data system is obtained. The stabilization problem of nonlinear sampled-data systems is considered under the low measurement rate constraint. Dual-rate control schemes based on the emulation design and discrete-time design approaches respectively are proposed that utilize a numerical integration model to approximately predict the current state of the plant. It is shown that using the dual-rate control schemes, input-to-state stability property will be preserved for the closed loop sampled-data system in a practical sense. On the other hand, the networked realization of nonlinear control systems is studied and a model-based control scheme is addressed as a solution to reduce the network traffic and resultantly, to attain a higher performance. The NCSs are modeled as continuous-time systems and sampled-data systems, respectively. Under the proposed control scheme, a tradeoff between satisfactory control performance and reduction of network traffic can be achieved. It is shown that by using the estimated values, generated by the plant model, instead of true values of the plant, a significant saving in the required bandwidth is achieved and this makes possible stabilization of the plant even under slow network conditions.

Research Doctorate - Doctor of Philosophy (PhD) / This thesis studies control systems with communication constraints. Such constraints arise due to the fact that practical control systems often use non-transparent communication links, i.e., links subject to data-rate constraints, random data-dropouts or random delays. Traditional control theory cannot deal with such constraints and the need for new tools and insights arises. We study two problems: control with average data-rate constraints and control over analog erasure channels with i.i.d. dropout profiles. When focusing on average data-rate constraints, it is natural to ask whether information theoretic ideas may assist the study of networked control systems. In this thesis we show that it is possible to use fundamental information theoretic concepts to arrive at a framework that allows one to tackle performance related control problems. In doing so, we show that there exists an exact link between control systems subject to average data-rate limits, and control systems which are closed over additive i.i.d. noise channels subject to a signal-to-noise ratio constraint. On the other hand, in the case of control systems subject to i.i.d. data-dropouts, we show that there exists a second-order moments equivalence between a linear feedback system which is interconnected over an analog erasure channel, and the same system when it is interconnected over an additive i.i.d. noise channel subject to a signal-to-noise ratio constraint. From the results foreshadowed above, it follows that the study of control systems closed over signal-to-noise ratio constrained additive i.i.d. noise channels is a task of relevance to many networked control problems. Moreover, the interplay between signal-to-noise ratio constraints and control objectives is an interesting issue in its own right. This thesis starts with such a study. Then, we use the resultant insights to address performance issues in control systems subject to either average data-rate constraints or i.i.d. data-dropouts. Our approach shows that, once key equivalences are exposed, standard control intuition and synthesis machinery can be used to tackle networked control problems in an exact manner. It also sheds light into fundamental results in the literature and gives (partial) answers to several previously open questions. We believe that the insights in this thesis are of fundamental importance and, to the best of the author's knowledge, novel.

As the Internet has grown to represent arguably the largest “engineered” system on earth, network researchers have shown increasing interest in measuring this large-scale networked system. In the process, structures such as the physical Internet or the many different (logical) overlay networks that this physical infrastructure enables have been the focus of numerous studies. Many of these studies have been fueled by the ease of access to “big data”. Moreover, they benefited from advances in the study of complex networks. However, an important missing aspect in typical applications of complex network theory to the study of real-world distributed systems has been a general lack of attention to domain knowledge. On the one hand, missing or superficial domain knowledge can negatively affect the studies “input”; that is, limitations or idiosyncrasies of the measurement methods can render the resulting graphs difficult to interpret if not meaningless. On the other hand, lacking or insufficient domain knowledge can result in specious “output”; that is, popular graph abstractions of real-world systems are incapable of accounting for “details” that are important from an engineering perspective. In this thesis, we take a closer look at measurement-based characterization of a few real-world large-scale networked systems and focus on the role that domain knowledge plays in gaining a thorough understanding of these systems key properties and behavior. More specifically, we use domain knowledge to (i) design context-aware measurement strategies that capture the relevant information about the system of interest, (ii) analyze the captured view of the networked system baring in mind the abstraction imposed by the chosen graph representation, and (iii) scrutinize the results derived from the analysis of the graph-based representations by investigating the root causes underlying these findings. The main technical contribution of our work is twofolds. First, we establish concrete connections between the amount and level of domain knowledge needed and the quality of the measurements collected from networked systems. Second, we also provide concrete evidence for the role that domain knowledge plays in the analysis of views inferred from measurements collected from large-scale networked systems

Networked control systems (NCSs) are known as distributed control systems (DCSs) which are based on traditional feedback control systems but closed via a real-time communication channel. In an NCS, the control and feedback signals are exchanged among the system’s components in the form of information packages through the communication channel. The research of NCSs is important from the application perspective due to the significant advantages over the traditional point-to-point control. However, the insertion of the communication links would also bring challenges and constraints such as the network-induced delays, the missing packets, and the inter symbol interference (ISI) into the system design. In order to tackle these issues and move a step further toward industry applications, two important design problems are investigated in the control areas: Tracking Control (Chapter 2–Chapter 5) and Signal Estimation (Chapter 6–Chapter8). With the fact that more than 90% of control loops in industry are controlled by proportional-integral-derivative (PID) controllers, the first work in this thesis aims to propose the design algorithm on PID controllers for NCSs. Such a design will not require the change or update of the existing industrial hardware, and it will enjoy the advantages of the NCSs. The second motivation is that, due to the network-induced constraints, there is no any existing work on tuning the PID gains for a general NCS with a state-space model. In Chapter 2, the PID tracking control for multi-variable NCSs subject to time-varying delays and packet dropouts is exploited. The H_infty control is employed to attenuate the load disturbance and the measurement noise. In Chapter 3, the probabilistic delay model is used to design the delay-scheduling tracking controllers for NCSs. The tracking control strategy consists of two parts: (1) the feedforward control can enhance the transient response, and (2) the feedback control is the digital PID control. In order to compensate for the delays on both communication links, the predictive control scheme is adopted. To make full use of the delay information, it is better to use the Markov chain to model the network-induced delays and the missing packets. A common assumption on the Markov chain model in the literature is that the probability transition matrix is precisely known. However, the assumption may not hold any more when the delay is time-varying in a large set and the statistics information on the delays is inadequate. In Chapter 4, it is assumed that the transition matrices are with partially unknown elements. An observer-based robust energy-to-peak tracking controller is designed for the NCSs. In Chapter 5, the step tracking control problem for the nonlinear NCSs is in- vestigated. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy linear model. The control strategy is a modified PI control. With an augmentation technique, the tracking controller design problem is converted into an H_infty optimization problem. The controller parameters can be obtained by solving non-iterative linear matrix inequality conditions. The state estimation problem for networked systems is explored in Chapter 6. At the sensor node, the phenomenon of multiple intermittent measurements is considered for a harsh sensing environment. It is assumed that the network-induced delay is time- varying within a bounded interval. To deal with the delayed external input and the non-delayed external input, a weighted H_infty performance is defined. A Lyapunov- based method is employed to deal with the estimator design problem. When the delay is not large, the system with delayed state can be transformed into delay-free systems. By using the probabilistic delay model and the augmentation, the H_infty filter design algorithm is proposed for networked systems in Chapter 7. Considering the phenomenon of ISI, the signals transmitted over the communication link would distort, that is, the output of the communication link is not the same with the input to the communication link. If the phenomenon occurs in the NCSs, it is desired to reconstruct the signal. In Chapter 8, a robust equalizer design algorithm is proposed to reconstruct the input signal, being robust against the measurement noise and the parameter variations. Finally, the conclusions of the dissertation are summarized and future research topics are presented. / Graduate

With the help of rapidly advancing communication technology, control systems are increasingly integrated via communication networks. Networked control systems (NCSs) bring significant advantages such as flexible and scalable structures, easy implementation and maintenance, and efficient resources distribution and allocation. NCSs empowers to finish some complicated tasks using some relatively simple systems in a collaborated manner. However, there are also some challenges and constraints subject to the imperfection of communication channels. In this thesis, the stabilization problems and the performance limitation problems of control systems subject to networked-induced constraints are studied. Overall, the thesis mainly includes two parts: 1) Consensus and consensusability of multi-agent systems (MASs); 2) Delay margins of NCSs. Chapter 2 and Chapter 3 deal with the consensus problems of MASs, which aim to properly design the control protocols to ensure the state convergence of all the agents. Chapter 4 and Chapter 5 focus on the consensusability analysis, exploring how the dynamics of the agents and the networked induced constraints impact the overall systems for achieving consensus. Chapter 6 pays attention to the delay margins of discrete-time linear time-invariant (LTI) systems, studying how the dynamics of the plants limit the time delays that can be tolerated by LTI controllers. In Chapter 2, the leader-following consensus problem of MASs with general linear dynamics and arbitrary switching topologies is considered. The MAS with arbitrary switching topologies is formulated as a switched system. Then the leaderfollowing consensus problem is transformed to the stability problem of the corresponding switched system. A necessary and sufficient consensus condition is derived. The condition is also extended to MASs with time-varying delays. In Chapter 3, the consensus problem of MASs with general linear dynamics is studied. Motivated by the multiple-input multiple-output (MIMO) communication technique, a general framework is considered in which different state variables are exchanged in different independent communication topologies. This novel framework could improve the control system design flexibility and potentially improve the system performance. Fully distributed consensus protocols are proposed and analyzed for the settings of fixed and switching multiple topologies. The protocols can be applied using only local information. And the control gains can be designed depending on the dynamics of the individual agent. By transforming the overall MASs into cascade systems, necessary and sufficient conditions are provided to guarantee the consensus under fixed and switching state-variables-dependent topologies, respectively. Chapter 4 investigates the consensusability problem for MASs with time-varying delays. The bounded delays can be arbitrarily fast time-varying. The communication topology is assumed to be undirected and fixed. Considering general linear dynamics under average state protocols, the consensus problem is then transformed into a robust control problem. Sufficient frequency domain criteria are established in terms of small-gain theorem by analyzing the delay dependent gains for both continuoustime and discrete-time systems. The controller synthesis problems can be solved by applying the frequency domain design methods. The consensusablity problem of general linear MASs considering directed topologies are explored from a frequency domain perspective in Chapter 5. By investigating the properties of Laplacian spectra, a consensus criterion is established based on the stability of several complex weighted closed-loop systems. Furthermore, for singleinput MASs, frequency domain consensusability criteria are proposed on the basis of the stability margins, which depend on the H∞ norm of the complementary sensitivity function determined by the agents’ unstable poles. The corresponding design procedure is also developed. Chapter 6 studies the delay margin problem of discrete-time LTI systems. For general LTI plants with multiple unstable poles and nonminimum phase zeros, we employ analytic function interpolation and rational approximation techniques to derive bounds on delay margins. Readily computable and explicit lower bounds are found by computing the real eigenvalues of a constant matrix, and LTI controllers can be synthesized based on the H∞ control theory to achieve the bounds. The results can be also consistently extended to the case of systems with time-varying delays. For first-order unstable plants, we also obtain bounds achievable by proportionalintergral- derivative (PID) controllers, which are of interest to PID control design and implementation. It is worth noting that unlike its continuous-time counterpart, the discrete-time delay margin problem being considered herein constitutes a simultaneous stabilization problem, which is known to be rather difficult. While previous work on the discrete-time delay margin led to negative results, the bounds developed in this chapter provide instead a guaranteed range of delays within which the delayed plants can be robustly stabilized, and in turn solve the special class of simultaneous stabilization problems in question. Finally, in Chapter 7, the thesis is summarized and some future research topics are also presented. / Graduate

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The complexity of networked systems has been continuously growing, and the abundance of online resources has presented practical management challenges. Specifically, system administrators are required to carefully configure their online systems to minimize security vulnerabilities of resource management, including resource creation, maintenance, and disposal. However, numerous networked systems have been exploited or compromised by adversaries, due to misconfiguration and mismanagement of human errors. In this dissertation, we explore different network systems to identify security vulnerabilities that adversaries could exploit for malicious purposes. First, we investigate the identity-account inconsistency threat, a new SSO vulnerability that can cause the compromise of online accounts. We demonstrate that this inconsistency in SSO authentication allows adversaries controlling a reused email address to take over online accounts without using any credentials. To substantiate our findings, we conduct a measurement study on the account management policies of various cloud email providers, highlighting the feasibility of acquiring previously used email accounts. To gain insight into email reuse in the wild, we examine commonly employed naming conventions that contribute to a significant number of potential email address collisions. To mitigate the identity-account inconsistency threat, we propose a range of useful practices for end-users, service providers, and identity providers. Secondly, we present a comprehensive study on the vulnerability of container registries to typosquatting attacks. In typosquatting attacks, adversaries intentionally upload malicious container images with identifiers similar to those of benign images, leading users to inadvertently download and execute malicious images. Our study demonstrates that typosquatting attacks can pose a significant security threat across public and private container registries, as well as across multiple platforms. To mitigate the typosquatting attacks in container registries, we propose CRYSTAL, a lightweight extension to the existing Docker command-line interface. Thirdly, we present an in-depth study on hardware resource management in cloud gaming services. Our research uncovers that adversaries can intentionally inject malicious programs or URLs into these services using game mods. To demonstrate the severity of these vulnerabilities, we conduct four proof-of-concept attacks on cloud gaming services, including crypto-mining, machine-learning model training, Command and Control, and censorship circumvention. In response to these threats, we propose several countermeasures that cloud gaming services can implement to safeguard their valuable assets from malicious exploitation. These countermeasures aim to enhance the security of cloud gaming services and mitigate the security risks associated with hardware mismanagement. Last but not least, we present a comprehensive and systematic study on NXDomain, examining its scale, origin, and security implications. By leveraging a large-scale passive DNS database, we analyze a vast dataset spanning from 2014 to 2022, identifying an astonishing 146 trillion NXDomains queried by DNS users. To gain further insights into the usage patterns and security risks associated with NXDomains, we carefully select and register 19 NXDomains in the DNS database. To analyze the behavior and sources of these queries, we deploy a honeypot for our registered domains and collect 5,925,311 queries over a period of six months. Furthermore, we conduct extensive traffic analysis on the collected data, uncovering various malicious uses of NXDomains, including botnet takeovers, malicious file injections, and exploitation of residual trust. / Doctor of Philosophy / This dissertation investigates the security risks arising from resource management in various network systems. On the one hand, we explore the security risks of software resource mismanagement, examining two specific threats: the identity-account inconsistency threat in Single Sign-On authentication schemes and the typosquatting attack in container registries. On the other hand, we investigate hardware resource misuse in network systems, focusing on two security issues: the exploitation of computing hardware in cloud gaming services and the analysis of NXDomains within the Domain Name System (DNS). By thoroughly analyzing and understanding these security risks, this dissertation contributes to the advancement of networked system security and provides necessary countermeasures to protect Internet users against these threats.

With the advancement of technology, there has been a push to transition from the conventional electric grid to a smart grid. A smart grid is an electric delivery system that uses technology such as electronic sensors and digital communication networks to improve the reliability, resilience, and efficiency of the system. The transition toward a smart grid has increased the importance of networked control systems (NCS), which are the infrastructure that allows sensors, actuators and controllers to exchange information via a digital communication network. The research presents the development of an islanded generator NCS, and a grid connected NCS, and the investigation of the effects of cyberattacks on the NCS. This research considers two types of cyberattacks, such as Denial-of-Service (DoS) attack, and false data injection in the generator control loop. DoS attacks greatly increase the rate of packet loss and the duration of packet delay in a network. A high degree of packet drop and delay degrade the performance of the controller, which causes problems in the synchronization of the generator with the rest of the grid. False data injection in the sensors alters the generator terminal voltage and power output, and can cause the generator to lose synchronism. A mathematical model of the generator NCS systems is developed which includes the data acquisition and network characteristics, as well as the generator dynamics. The stability analysis of each NCS is performed which provides a mathematical approach to understanding the severity of cyberattacks that the system can tolerate before becoming unstable. The performance of the controllers, with respect to voltage control, is experimentally evaluated. / Educational Psychology