Com as evoluções tecnológicas nas áreas de hardware, microeletrônica, sistemas de informação e computação, o conceito de sistemas ciberfísicos (do inglês Cyber-Physical Systems) vem ganhando importância. Este sistemas se referem à junção entre sistemas computacionais distribuídos e processos físicos da natureza e, são base fundamental para a nova revolução industrial que esta sendo introduzida. Esta revolução industrial é marcada pela completa descentralização do controle dos processos produtivos e uma proliferação de dispositivos inteligentes interconectados, ao longo de toda a cadeia de produção e logística. Sistemas de automação, e particularmente os sistemas de automação industrial, nos quais elementos computacionais controlam e automatizam a execução de processos físicos em plantas industriais, são um exemplo de sistemas ciber-físicos. Com isso, percebe-se que é necessário relacionar objetos físicos a informações associadas a este objeto no mundo cibernético. Para isso, destaca-se o conceito e o uso do Digital Twin, que é uma representação virtual de objetos físicos. O Digital Twin possibilita a virtualização e centralização do controle no produto. Este estudo irá explorar uma metodologia de modelagem genérica e flexível para o Digital Twin usando a ferramenta AutomationML e propor uma arquitetura de comunicação para a troca de dados sob a ótica de Cyber Physical Systems. Com a implementação dessa metodologia, pretende-se validar o conceito proposto e oferecer um método de modelagem e configuração para obter dados, extrair conhecimento e proporcionar sistemas de visualização para os usuários. / With technological advances in the fields of hardware, microelectronics and computer systems, Cyber Physical Systems is a new concept that is gaining importance. This systems are integrations of computation, networking, and physical processes. Cyber Physical Systems are one of the pillars for the new industrial revolution, and it is marked by the complete decentralization of the control of production processes and, marked by a proliferation of interconnected intelligent devices throughout the production and logistics chain. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. A industrial automation system, is an example of cyber physical systems where computational elements control and automate the execution of physical processes in industrial plants. Thus, it is clear the need to relate physical objects to information associated with this object in the cyber world. For this, this work pretends to use the concept of Digital Twin, that is a virtual representation of physical objects. Digital Twin enables the virtualization of physical components and descentralization of control. This study will explore a generic and flexible modeling methodology for Digital Twin using the AutomationML tool. Also this work proposes a communication architecture for the exchange of data from the perspective of Cyber Physical Systems. With the implementation of this methodology, we intend to validate the proposed concept and offer a modeling and configuration method to obtain data, extract knowledge and provide visualization systems for users.

Doctor of Philosophy / Electrical and Computer Engineering / Balasubramaniam Natarajan / A cyber-physical system (CPS) typically consists of networked computational elements that control physical processes. As an integral part of CPS, the widespread deployment of communicable sensors makes the task of monitoring and control quite challenging especially from the viewpoint of scalability and complexity. This research investigates two unique aspects of overcoming such barriers, making a CPS more robust against data explosion and network vulnerabilities. First, the correlated characteristics of high-resolution sensor data are exploited to significantly reduce the fused data volume. Specifically, spatial, temporal and spatiotemporal compressed sensing approaches are applied to sample the measurements in compressed form. Such aggregation can directly be used in centralized static state estimation even for a nonlinear system. This approach results in a remarkable reduction in communication overhead as well as memory/storage requirement. Secondly, an agent based architecture is proposed, where the communicable sensors (identified as agents) also perform local information processing. Based on the local and underdetermined observation space, each agent can monitor only a specific subset of global CPS states, necessitating neighborhood information exchange. In this framework, we propose an agent based static state estimation encompassing local consensus and least square solution. Necessary bounds for the consensus weights are obtained through the maximum eigenvalue based convergence analysis and are verified for a radial power distribution network. The agent based formulation is also applied for a linear dynamical system and the consensus approach is found to exhibit better and more robust performance compared to a diffusion filter. The agent based Kalman consensus filter (AKCF) is further investigated, when the agents can choose between measurements and/or consensus, allowing the economic allocation of sensing and communication tasks as well as the temporary omission of faulty agents. The filter stability is guaranteed by deriving necessary consensus bounds through Lyapunov stability analysis. The states dynamically estimated from AKCF can be used for state-feedback control in a model predictive fashion. The effect of lossy communication is investigated and critical bounds on the link failure rate and the degree of consensus that ensure stability of the agent based control are derived and verified via simulations.

abstract: Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities. For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting. For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control. The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

abstract: Despite incremental improvements over decades, academic planning solutions see relatively little use in many industrial domains despite the relevance of planning paradigms to those problems. This work observes four shortfalls of existing academic solutions which contribute to this lack of adoption. To address these shortfalls this work defines model-independent semantics for planning and introduces an extensible planning library. This library is shown to produce feasible results on an existing benchmark domain, overcome the usual modeling limitations of traditional planners, and accommodate domain-dependent knowledge about the problem structure within the planning process. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2016

abstract: A Cyber Physical System consists of a computer monitoring and controlling physical processes usually in a feedback loop. These systems are increasingly becoming part of our daily life ranging from smart buildings to medical devices to automobiles. The controller comprises discrete software which may be operating in one of the many possible operating modes and interacting with a changing physical environment in a feedback loop. The systems with such a mix of discrete and continuous dynamics are usually termed as hybrid systems. In general, these systems are safety critical, hence their correct operation must be verified. Model Based Design (MBD) languages like Simulink are being used extensively for the design and analysis of hybrid systems due to the ease in system design and automatic code generation. It also allows testing and verification of these systems before deployment. One of the main challenges in the verification of these systems is to test all the operating modes of the control software and reduce the amount of user intervention. This research aims to provide an automated framework for the structural analysis and instrumentation of hybrid system models developed in Simulink. The behavior of the components introducing discontinuities in the model are automatically extracted in the form of state transition graphs. The framework is integrated in the S-TaLiRo toolbox to demonstrate the improvement in mode coverage. / Dissertation/Thesis / Masters Thesis Computer Science 2016

abstract: Cyber-Physical Systems (CPS) are being used in many safety-critical applications. Due to the important role in virtually every aspect of human life, it is crucial to make sure that a CPS works properly before its deployment. However, formal verification of CPS is a computationally hard problem. Therefore, lightweight verification methods such as testing and monitoring of the CPS are considered in the industry. The formal representation of the CPS requirements is a challenging task. In addition, checking the system outputs with respect to requirements is a computationally complex problem. In this dissertation, these problems for the verification of CPS are addressed. The first method provides a formal requirement analysis framework which can find logical issues in the requirements and help engineers to correct the requirements. Also, a method is provided to detect tests which vacuously satisfy the requirement because of the requirement structure. This method is used to improve the test generation framework for CPS. Finally, two runtime verification algorithms are developed for off-line/on-line monitoring with respect to real-time requirements. These monitoring algorithms are computationally efficient, and they can be used in practical applications for monitoring CPS with low runtime overhead. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2017

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-05-04T17:30:47Z No. of bitstreams: 1 ALDENOR FALCÃO MARTINS – DISSERTAÇÃO (PPGEE) 2015.pdf: 15602466 bytes, checksum: 608173ca67ff68da8ae45b321aa82204 (MD5) / Made available in DSpace on 2018-05-04T17:30:47Z (GMT). No. of bitstreams: 1 ALDENOR FALCÃO MARTINS – DISSERTAÇÃO (PPGEE) 2015.pdf: 15602466 bytes, checksum: 608173ca67ff68da8ae45b321aa82204 (MD5) Previous issue date: 2015-04-24 / Segundo o IBGE em 2013, o Brasil apresentava 13% de sua população composta por pessoas acima de 65 anos, somado a isto, o estilo de vida das sociedades ocidentais tem facilitado o aparecimento de doenças crônicas cada vez mais cedo. A premissa é que tornemos mais eficiente a utilização do nosso sistema de saúde, pois este é um recurso escasso. Uma forma de melhorar esta eficiência é assegurar que os tratamentos prescritos serão devidamente seguidos. Quando o paciente se encontra no hospital uma gama de recursos monitora a saúde do paciente oferecendo acompanhamento seguro na eventualidade de um desvio, alertando e armazenando as informações do paciente no decorrer de suas atividades. Um recurso que ajuda no acompanhamento deste paciente é a monitoração remota do paciente, que possibilita que sensores enviem a informação da condição de saúde do paciente e permitam o acompanhamento do mesmo. Sistemas Físicos Cibernéticos (SFC) são entidades computacionais ligadas em rede que operam entidades no mundo físico de maneira cooperativa. Tais sistemas podem ser utilizados em redes de monitoramento remoto de pacientes com o fim de apresentar e ajustar o tratamento de acordo com as recomendações do médico. Este trabalho propõe um passo na direção da autonomia, que permita uma melhor qualidade de vida ao paciente crônico, permitindo que situações conhecidas e dentro de um regime de segurança previamente determinado pelo médico sejam ajustadas. Este trabalho apresenta uma proposta de um Sistema Físico Cibernético (SFC), que permite que adequações ao tratamento previamente elaboradas sejam colocadas em planos de tratamento por meio de agentes inteligentes e de planejadores SAT e sejam disponibilizadas de acordo com a mudança da condição do paciente, através de uma rede monitoramento do paciente, seguindo padrões estabelecidos para dispositivos médicos utilizados em casa que disponibiliza o tratamento ao paciente. O modelo proposto é indicado para o acompanhamento em casa de doenças crônicas através de um coletor central responsável pela coordenação do acompanhamento do paciente. / According to IBGE in 2013 13% of the population had 60 or more years old. As the national population ages, we have to move towards more efficient use of SUS. A way to improve is the closer followup of patient’s evolution by the healthcare professional. At the hospital the patient has access to a set of equipments and expert knowledge capable to correct the treatment path. From this scenario it is easy to imply the need for a change, the current status quo is unbearable financially and cumbersome for patient and doctor routines. A resource that helps is the remote patient monitoring (RPM) , where sensors provide the latest information about patient’s health status and are able to suggest a course correction on the treatment path. A Cyber-Physical System (CPS) is a network of interacting computational entities with physical inputs and outputs that work together towards a goal. A CPS can be part of a RPM in order to present and adjust the treatment according to the healthcare professional recommendations. This work offers a framework for situations where the medical expert knowledge is complete allowing changes on the treatment path be adjusted with minimum risk. Our proposal to deal with the problem is a CPS based remote patient monitoring network where a model for the system is developed based on Multiagent Agent System (MAS) and automatic planning system based on SAT, allowing safe and minimal course correction on treatment paths already set for a patient. This proposal operates through a central hub element responsible to coordinate the followup of the patient.

abstract: This thesis introduces the Model-Based Development of Multi-iRobot Toolbox (MBDMIRT), a Simulink-based toolbox designed to provide the means to acquire and practice the Model-Based Development (MBD) skills necessary to design real-time embedded system. The toolbox was developed in the Cyber-Physical System Laboratory at Arizona State University. The MBDMIRT toolbox runs under MATLAB/Simulink to simulate the movements of multiple iRobots and to control, after verification by simulation, multiple physical iRobots accordingly. It adopts the Simulink/Stateflow, which exemplifies an approach to MBD, to program the behaviors of the iRobots. The MBDMIRT toolbox reuses and augments the open-source MATLAB-Based Simulator for the iRobot Create from Cornell University to run the simulation. Regarding the mechanism of iRobot control, the MBDMIRT toolbox applies the MATLAB Toolbox for the iRobot Create (MTIC) from United States Naval Academy to command the physical iRobots. The MBDMIRT toolbox supports a timer in both the simulation and the control, which is based on the local clock of the PC running the toolbox. In addition to the build-in sensors of an iRobot, the toolbox can simulate four user-added sensors, which are overhead localization system (OLS), sonar sensors, a camera, and Light Detection And Ranging (LIDAR). While controlling a physical iRobot, the toolbox supports the StarGazer OLS manufactured by HAGISONIC, Inc. / Dissertation/Thesis / Model-Based Development of Multi-iRobot Toolbox (version 1.0) / M.S. Computer Science 2012

abstract: A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

abstract: With growing complexity of power grid interconnections, power systems may become increasingly vulnerable to low frequency oscillations (especially inter-area oscillations) and dependent on stabilizing controls using either local signals or wide-area signals to provide adequate damping. In recent years, the ability and potential to use wide-area signals for control purposes has increased since a significant investment has been made in the U. S. in deploying synchrophasor measurement technology. Fast and reliable communication systems are essential to enable the use of wide-area signals in controls. If wide-area signals find increased applicability in controls the security and reliability of power systems could be vulnerable to disruptions in communication systems. Even though numerous modern techniques have been developed to lower the probability of communication errors, communication networks cannot be designed to be always reliable. Given this background the motivation of this work is to build resiliency in the power grid controls to respond to failures in the communication network when wide-area control signals are used. In addition, this work also deals with the delay uncertainty associated with the wide-area signal transmission. In order to counteract the negative impact of communication failures on control effectiveness, two approaches are proposed and both approaches are motivated by considering the use of a robustly designed supplementary damping control (SDC) framework associated with a static VAr compensator (SVC). When there is no communication failure, the designed controller guarantees enhanced improvement in damping performance. When the wide-area signal in use is lost due to a communication failure, however, the resilient control provides the required damping of the inter-area oscillations by either utilizing another wide-area measurement through a healthy communication route or by simply utilizing an appropriate local control signal. Simulation results prove that with either of the proposed controls included, the system is stabilized regardless of communication failures, and thereby the reliability and sustainability of power systems is improved. The proposed approaches can be extended without loss of generality to the design of any resilient controller in cyber-physical engineering systems. / Dissertation/Thesis / Ph.D. Electrical Engineering 2014