Analysis and Control for Resilience of Discrete Event Systems

Abstract: One of the important features of a smart grid is a periphery that is becoming increasingly intelligent. High penetration of renewable energy based generation in distribution grid can introduce significant challenges for carrying out efficient Volt/Var Control. One of the main difficulties is the associated uncertainties and intermittencies which can cause voltage regulation to be quite difficult. Demand Response, where consumption is made flexible, can help ease this diifficulty. In this talk, the use of smart buildings, that represent one of the main building blocks of Demand Response for voltage regulation will be explored. In particular, how these units can be integrated in a Distribution Grid for better voltage regulation will be examined.

Abstract: This talk discusses how notions of opacity can be used to capture, analyse, and enforce privacy/security properties in emerging interconnected discrete event systems. More specifically, we start with an overview language and state-based opacity, as well as extensions to probabilistic and timed systems. To illustrate these formulations, we focus on systems that are described by (nondeterministic) automata and assume that a passive intruder observes system activity through some natural projection mapping, using knowledge of the system model in order to make inferences about the possible state of the system. The talk discusses methods to verify state-based notions of opacity (including current-state opacity, initial-state opacity, K-step opacity, and infinite-step opacity) using various types of state estimators. Several examples are used to illustrate how such notions can be used to characterize privacy and security requirements in many applications of interest, including encryption using pseudo-random generators, coverage of mobile agents in sensor networks, and anonymity requirements in protocols for web transactions.​

Abstraction: One of the major challenges about cyber physical systems is how to protect system integrity from cyber attacks. There has been a large number of different types of attacks discussed in the literature. In this talk I will discuss several types of attacks in the discrete-event system framework, namely covert sensor attacks, where an attacker can arbitrarily alter sensor readings after intercepting them from a target system, aiming to trick a given supervisor to issue improper control commands, which can drive the system to an undesirable state; covert actuator attacks, where an attacker intercepts control commands and alter their contents to trigger damages to the plant without being detected by the supervisor; and covert channel delay attacks, where an attacker deliberately delays (but not change) sensor readings to alter the sequence of observations to in ict damages to the plant without being detected by the supervisor. I will first describe relevant attack models, and present the key concepts of attackability associated with different attacks. Then I will present specific algorithms to synthesize covert attack models. Finally, I will address the resilience issue, and present results about existence of attack-resilient supervisors.

Abstract: Diagnosability is a property of discrete event systems (DES) that ensures that the occurrence of an unobservable failure event is detect after the occurrence of a finite number of events after the failure. Failures in DES are detected online by using a so-called diagnoser automaton, which is actually an observer automaton that not only keeps track of the system state evolution but also has labels that inform whether the system is working within its normal or faulty behavior. However, diagnosers are built assuming exact knowledge of the model of the real plant, and, when, for some reason, the model does not correspond to the actual system behavior, diagnosers may either issue wrong information regarding the failure occurrence or halt in some state; even though the real system continues evolving. In order to overcome these problems, robust diagnosers have been proposed, whose central idea is to ensure the correct functioning of the diagnosis system by taking in consideration not only the plant nominal behavior but also additional information regarding the system functioning and its components. In this talk we address the problem of robust failure diagnosis under the following perspectives: (i) assuming that the communication between local sites and coordinator is not reliable in decentralized systems; (ii) assuming intermittent and permanent sensor failures; (iii) assuming communication delays between measurements sites and local diagnosers in networked DES. We end this talk by also considering decentralized diagnosis of networked DES subject to denial of service attacks, a problem of current interest, being motivated by the increase in the use of communication network for supervision and control of physical system, which increases the vulnerability of these cyber-physical systems since an outsider may interfere in the desired behavior of the system.

Abstract: As distributed energy resources (DERs) are becoming prevalent in power distribution systems, various control schemes have been developed to engage various DERs ranging from the small-sized resources (end-use appliances, electric vehicle, energy storage, etc.) to large-sized resources (residential and commercial building) in participating into grid operations. Among these proposed control strategies, transactive coordination and control have attracted consid- erable research attentions. It uses economic or market-like constructs to manage distributed smart grid assets and is amenable to problems where self-interested entities are coordinated to achieve global control objectives. Transactive control framework actually complements the conventional centralized control framework associated with direct load control. It is based on dis- tributed control and has the significant advantages of scalability, exibility and interoperability. Furthermore, it fully respect individual entities preference and privacy. In this presentation, the latest development of behind-the-meter transactive design for smart buildings will be discussed. Field demonstration results will also be presented to illustrate the effectiveness of transactive control design for demand response.

Abstract: Smart building technology has allowed for advancements in the integration and holis- tic control of building services to provide a higher standard of living for its occupants. Addi- tionally, smart building technology provides unparalleled control and data about the occupants behavior. These advancements are essential for numerous societal challenges, such as decar- bonization, reduction of water consumption, and chronic diseases. Individual household level innovation has led to opportunities to further society as a whole. Smart buildings, consequently, dont operate in a vacuum. Infrastructure systems enable smart buildings by providing critical services such as electric power, natural gas, potable water, wastewater collection, and trans- portation. These infrastructures are interdependent, and the interface with a smart building is just one such example. The existing literature has struggled to integrate interdependent in- frastructures and assess them as one, whereas smart buildings prove that there is need for an integrated approach. This workshop presentation expands the system boundary beyond the building level, to look at the interfaces of smart buildings to a smart citys interdependent in- frastructure systems. Hetero-functional graph theory provides a novel mathematical framework to model interdependent smart city infrastructure systems. Rooted in the establishedf fields of Graph Theory, Axiomatic Design, and Systems Engineering, it facilitates the construction of a single mathematical model that incorporates multiple, unlike engineering systems. Recent ap- plications include the energy-water nexus, electrified transportation, and interdependent smart city infrastructures. Smart buildings interact with all smart city infrastructure systems and it is therefore necessary to investigate their integration with the surrounding context.

Abstract: Many emergencies require people to evacuate a building quickly. During an emer- gency, evacuees tend to rely on default decision making, such as exiting the way they entered, following a crowd, or sheltering in place, which may put them in danger. When a crowd attempts to exit through a single exit, choke points and crowd congestion may impede the safe ow of evacuees, potentially resulting in a stampede of people and the loss of human lives. Nowadays more and more situations demand a quick, coordinated evacuation of hundreds or thousands of people. In this talk, we will introduce our recent work on using mobile robots to direct evacuees for a rapid and orderly evacuation. Emergency response robots may save human lives by quickly guiding people to open exits. Particularly, we focused on the mathematical modeling of human crowd and investigate how to optimally deploy robots to guide human crowds in an efficient and safe manner during an evacuation process. Inspired by social force model and mean field game theory, we model pedestrians as Brownian agents using stochatsic differential equations. We further incorporate the impact of the robots in the Brownian agent model for the microscopic individual pedestrian and obtain the corresponding Kolmogorov equation to describe the crowd dynamics evolution at the macroscopic level. Then, a two-step hierarchical structure is proposed to solve the robot deployment and command selection problem based on our modeling framework. We are also going to discuss some encouraging simulation results and potential future directions.

Abstract: A fault-tolerant supervisory controller maintains a prescribed closed-loop performance even when the plant is subject to certain faults. In this workshop, we discuss fault-tolerant supervisory control in terms of formal languages. Doing so, we obtain a general framework in which we can re-interpret established approaches like passive fault tolerance and active fault tolerance. Moreover, a synthesis algorithm for fault-tolerant supervisory controllers can be derived by minor variations of the base algorithms commonly used in the context of supervisory control. For the workshop format, we can present the approach in considerable detail and, hence, provide a technical introduction to fault-tolerant supervisory control.

Abstract: Machine learning methods applied to large data sets have transformed many scientific and engineering disciplines. Enormous data corporated from the built environment exist but the value of such information remains largely hidden and consequently, unexploited. In this talk, we will present our research in analytics engines to analyze building data with particular attention to the following issues: (1) Modeling occupant needs and preferences that can be fulfilled by intelligent building control systems, and their behavioral response to energy reduction incentives; (2) Assessing the system state for preventive maintenance scheduling and low-latency fault detection of building components; (3) Identifying characteristics of highly energy efficient buildings at the community-scale; (4) Making aggregate data and data analytics algorithms and software available to the community using widely acceptable open source principles.

Abstract: This talk presents an Internet of Things (IoT) prototype that implements a novel hierarchical control approach called the Token Based Scheduling Algorithm (TBSA) to save energy in heating, ventilation, and air-conditioning (HVAC) systems in commercial buildings. The IoT prototype is formalized with an architecture that encapsulates the different components (hardware, software and their integration) along with their interactions. A detailed description of these different components, communication among them as well with the cloud and legacy Building Automation System (BAS) is presented. In addition, the simple modifications to the existing HVAC control for translating TBSA from being an abstract optimization application to an active HVAC control strategy is presented. This involves experiments and non-intrusive modifications to the existing BAS control loops. The investigation also enhances the TBSA by including soft-constraints in the optimization model and recursive learning for updating zone thermal models in a large commercial building. Our investigation illustrates that by combining the IoT with the TBSA, an otherwise rigid and centralized BAS control architecture can be transformed to a more exible decentralized one. In addition, desirable features such as better scalability, engineering simplicity, and performance can be achieved by deploying upgrades on lowcost devices over legacy BAS. The IoT prototype and TBSA implementation are illustrated on a test-building in Nanyang Technological University, Singapore having 85 zones with variable air volume controlled HVAC system. Our results shows that the integration of IoT and TBSA meets the envisioned benefits such as scalability in terms of a number of zones, economic upgrade with faster payback times, and less disruptive modifications. The energy savings is around 20% in the test bed with an average payback time of 1-1.5 years.

Abstract: We consider feedback control systems where sensor readings may be compromised by a malicious attacker intent on causing damage to the system. We study this problem at the supervisory layer of the control system, using discrete transition models of the underlying plant dynamics. We assume that the attacker can edit the (discrete) outputs from the sensors of the system before they reach the supervisory controller. In this context, we discuss two researchproblems: (i) synthesis of stealthy or non-stealthy edit attacks; and (ii) synthesis of a supervisor that is robust against a class of edit attacks. The attack synthesis problem is analyzed under both logical and stochastic models of the plant. Then, two solution methodologies of the problem of robust supervisor synthesis are discussed. The results presented leverage concepts and algorithmic techniques from supervisory control theory and from logical and stochastic games on automata. This is a joint work with Romulo Meira-Goes, Eunsuk Kang, Raymond Kwong, and Herve Marchand.

Xiang Yin was born in Anhui, China, in 1991. He received the B.Eng degree from Zhejiang University in 2012, the M.S. degree from the University of Michigan, Ann Arbor, in 2013, and the Ph.D degree from the University of Michigan, Ann Arbor, in 2017, all in electrical engineering. Since 2017, he has been with the Department of Automation, Shanghai Jiao Tong University, where he is an Associate Professor. His research interests include formal methods, discrete-event systems and cyber-physical systems. Dr. Yin is serving as the co-chair of the IEEE CSS Technical Committee on Discrete Event Systems, an Associate Editor for the Journal of Discrete Event Dynamic Systems: Theory & Applications, and a member of the IEEE CSS Conference Editorial Board. Dr. Yin received the IEEE Conference on Decision and Control (CDC) Best Student Paper Award Finalistin 2016.

Joao Carlos Basilio received his bachelor degree in Electrical Engineering in 1986 from the Federal University of Juiz de Fora and master and PhD degrees, both in Control Systems, in 1989 and 1995, respectively, at the Military Engineering Institute, Rio de Janeiro, and at the University Oxford, Oxford, England. He began his career as Assistant Professor in the Department of Electrical Engineering of the Federal University of Rio de Janeiro in 1990, becoming Assistant Professor in 1996 and Associate Professor in 2006. He is currently Full Professor of the Polytechnic School of UFRJ. He was coordinator of the Control and Automation Engineering Course of the Polytechnic School / UFRJ in the 2005-2006 biennium, coordinator of the Graduate Program in Electrical Engineering of COPPE / UFRJ from January 2008 to February 2009, head of the Department of Electrical Engineering of the Polytechnic School from May 2012 to February 2014 and Director of the Polytechnic School of UFRJ from February 2014 to February 2018. He completed postdoctoral training at the University of Michigan from September 2007 to December of 2008 and was Guest Visiting Professor of the cole Centrale de Lille, University of Lille, France during the months of September 2016 and November 2018. His main interests are: fault diagnosis, opacity and supervisory control of systems to discrete events. Prof. Basilio was awarded in 1981 with the Correia Lima medal.

Christoforos Hadjicostis received S.B. degrees in Electrical Engineering, in Computer Science and Engineering, and in Mathematics, the M.Eng. degree in Electrical Engineering and Computer Science in 1995, and the Ph.D. degree in Electrical Engineering and Computer Science in 1999, all from the Massachusetts Institute of Technology, Cambridge, MA. In August 1999 he joined the Faculty at the University of Illinois at Urbana-Champaign (UIUC) where he reached the rank of Associate Professor with the Department of Electrical and Computer Engineering, Research Associate Professor with the Coordinated Science Laboratory, and Research Associate Professor with the Information Trust Institute. In 2007, Dr. Hadjicostis joined the Department of Electrical and Computer Engineering at the University of Cyprus, where he served as Chair of the ECE Department from 2008 to 2010, and as Dean of Engineering from 2014 to 2017. Dr. Hadjicostis teaches and conducts research in the areas of systems and control, communication, and digital signal processing. His current research focuses on fault diagnosis and tolerance in distributed dynamic systems; error control coding; distributed algorithms for monitoring, diagnosis and control; discrete event systems; and applications to network security, anomaly detection, medical diagnosis, and biosequencing. Dr. Hadjicostis serves as Departmental Editor of the Journal of Discrete Event Dynamic Systems and as Associate Editor for IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Automation Science and Engineering, and the Journal of Nonlinear Analysis: Hybrid Systems; he has also served as Associate Editor for the IEEE Transactions on Circuits and Systems I (Regular Papers), the IEEE Transactions on Control Systems Technology, and the Journal of Discrete Event Dynamic Systems, and as Editor on the Conference Editorial Board of the IEEE Control Systems Society. At the University of Illinois, Dr. Hadjicostis received the Faculty Early Development (CAREER) award from the National Science Foundation in February 2001, the ECE Faculty Outstanding Teaching Award in 2003, and the Willett Faculty Scholar recognition from the College of Engineering in 2005; at the University of Cyprus, he received a 2008 Marie Curie International Reintegration Fellowship from the European Commission. As a graduate student at MIT, he served as president of the MIT Chapter of HKN, received the Harold L. Hazen Teaching Award and the Ernst A. Guillemin Thesis Prize, and received fellowships from the National Semiconductor Corporation and the Grass Instrument Company. Dr. Hadjicostis is a member of Eta Kappa Nu and Sigma Xi, and a senior member of the IEEE.

Stephane Lafortune received the B.Eng degree from cole Polytechnique de Montral in 1980, the M.Eng degree from McGill University in 1982, and the Ph.D degree from the University of California at Berkeley in 1986, all in electrical engineering. Since September 1986, he has been with the University of Michigan, Ann Arbor, where he is a Professor of Electrical Engineering and Computer Science. In March 2018, he was appointed as the N. Harris McClamroch Collegiate Professor of Electrical Engineering and Computer Science. Lafortune is a Fellow of the IEEE (1999) and of IFAC (2017). He received the Presidential Young Investigator Award from the National Science Foundation in 1990 and the Axelby Outstanding Paper Award from the Control Systems Society of the IEEE in 1994 (for a paper co-authored with S.-L. Chung and F. Lin) and in 2001 (for a paper co-authored with G. Barrett). Lafortune's research interests are in discrete event systems and include multiple problem domains: modeling, diagnosis, control, optimization, and applications to computer and software systems. He is the lead developer of the software package UMDES and co-developer of DESUMA with L. Ricker. He co-authored, with C. Cassandras, the textbook Introduction to Discrete Event Systems (Second Edition, Springer, 2008). Lafortune is Editor-in-Chief of the Journal of Discrete Event Dynamic Systems: Theory and Applications.

Rong Su obtained his Bachelor of Engineering degree from University of Science and Technology of China in 1997, and Master of Applied Science degree and PhD degree from University of Toronto, in 2000 and 2004, respectively. He was aliated with University of Waterloo and Technical University of Eindhoven before he joined Nanyang Technological University in 2010. Currently, he is an associate professor in the School of Electrical and Electronic Engineering. Dr. Su's research interests include multi-agent systems, discrete-event system theory, resilient supervisory control, model-based fault diagnosis, operation planning and scheduling with applications in flexible manufacturing, intelligent transportation, human-robot interface, power management and green building. In the aforementioned areas he has more than 220 journal and conference publications, 1 monograph, and 6 granted/filed USA/Singapore patents. Dr. Su is a senior member of IEEE, and an associate editor for Automatica, Journal of Discrete Event Dynamic Systems: Theory and Applications, and Journal of Control and Decision. He was the chair of the Technical Committee on Smart Cities in the IEEE Control Systems Society in 2016-2019, and is currently a co-chair of the Technical Committee on Automation in Logistics in the IEEE Robotic and Automation Society, and the chair of IEEE Control Systems Chapter, Singapore.

Jianming (Jamie) Lian is currently a senior staff engineer in the Optimization and Control group at Pacific Northwest National Laboratory. He received the B.S. degree with the highest honor from University of Science and Technology of China in 2004. After that, he received the M.S. and the Ph.D. degree in Electrical Engineering from Purdue University, West Lafayette, IN, in 2007 and 2009, respectively. From 2010 to 2011, he worked as a postdoctoral research associate at Center for Advanced Power Systems in Florida State University, Tallahassee, FL, where he was involved in various projects related to the development of future all-electric ship supported by ONR. Since joining in PNNL, he has been serving as a project manager, PI/Co-PI and key technical contributor for many research projects in the areas of power grid, building system, and transportation system. In particular, he has been extensively working on the development of the theoretical foundation for the new market-based (aka, transactive) coordination and control to engage and integrate various distributed energy resources (DERs) into the future distribution management system.

(Samuel) Qing-Shan Jia received the B.E. degree in automation in July 2002 and the Ph.D. degree in control science and engineering in July 2006, both from Tsinghua University, Beijing, China. He is an Associate Professor in the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a visiting scholar at Harvard University in 2006, at the Hong Kong University of Science and Technology in 2010, and at Laboratory for Information and Decision Systems, Massachusetts Institute of Technology in 2013. His research interest is to develop an integrated data-driven, statistical, and computational approach to find designs and decision-making policies which have simple structures and guaranteed good performance. His work relies on strong collaborations with experts in manufacturing systems, energy systems, autonomous systems, and smart cities. He is an associate editor (AE) of IEEE Transactions on Automatic Control, and was an AE of IEEE Transactions on Automation Science and Engineering (2012-2017) and Discrete Event Dynamic Systems Theory and Applications (2012-2016). He served the Discrete Event Systems Technical Committee chair in IEEE Control Systems Society (2012-2015), and now serves the Control for Smart Cities Technical Committee chair in International Federation of Automatic Control, the Smart Buildings Technical Committee co-chair in IEEE Robotics and Automation Society, and the Beijing Chapter Chair of IEEE Control Systems Society. He is a member of the 11th Chinese Automation Association Technical Committee on Control Theory (2018- 2022) and the 1st Chinese Automation Association Technical Committee on Information Security of Industrial Systems (2016-2020).

Dr. Anuradha Annaswamy received the Ph.D. degree in Electrical Engineering from Yale University in 1985. She has been a member of the faculty at Yale, Boston University, and MIT where currently she is the director of the Active-Adaptive Control Laboratory and a Senior Research Scientist in the Department of Mechanical Engineering. Her research interests pertain to adaptive control theory and applications to aerospace and automotive control, active control of noise in thermo- uid systems, control of autonomous systems, decision and control in smart grids, smart cities, and critical infrastructures, and co-design of control and platform architectures in cyber physical systems. Dr. Annaswamy has received several awards including the George Axelby and Control Systems Magazine best paper awards from the IEEE Control Systems Society, the Presidential Young Investigator award from the National Science Foundation, the Hans Fisher Senior Fellowship from the Institute for Advanced Study at the Technische Universitt Mnchen in 2008, the Donald Groen Julius Prize for 2008 from the Institute of Mechanical Engineers, and the Distinguished Member award from the IEEE Control Systems Society in 2016. Dr. Annaswamy is a Fellow of the IEEE and IFAC. Dr. Annaswamy is an active member of the IEEE Control Systems Society (CSS) and the American Automatic Control Council. She was a nominated and elected member of the CSS Board of Governors for 1993 and 2010 2012, respectively. She was a Program Chair of the American Control Conference (ACC) during 2003, General Chair of the 2008 ACC, and Program Chair for the 2nd Virtual Control Conference on Smart Grid Technology. She served as the Vice-President for Conference Activities in the IEEE CSS Executive Committee for 2014-15. Dr. Annaswamy is a co-editor of the IEEE CSS report on Impact of Control Technology: Overview, Success Stories, and Research Challenges,2011 (1st Edition) and 2014 (2nd Edition) along with Tariq Samad. She is the project lead on the publication, Vision for Smart Grid Controls: 2030 and Beyond, (Eds: A.M. Annaswamy, M. Amin, C. DeMarco and T. Samad), 2013.

Costas J. Spanos received the EE Diploma from the National Technical University of Athens, Greece in 1980 and the M.S. and Ph.D. degrees in ECE from Carnegie Mellon University in 1981 and 1985, respectively. In 1988 he joined the Faculty at the department of Electrical Engineer- ing and Computer Sciences of the University of California at Berkeley. He has served as the Director of the Berkeley Microlab, the Associate Dean for Research in the College of Engineering and as the Chair of the Department of EECS. He works in statistical analysis in the design and fabrication of integrated circuits, and on novel sensors and computer-aided techniques in semiconductor manufac- turing. He also works on statistical data mining techniques for energy efficiency applications. He has participated in two successful startup companies, Timbre Tech, (acquired by Tokyo Electron) and OnWafer Technologies (acquired by KLA-Tencor). He is presently the Director of the Center of Information Technology Research in the Interest of Society (CITRIS) and the Chief Technical Officer for the Berkeley Educational Alliance for Research in Singapore (BEARS).

Alessandro Giua is professor of Automatic Control at the Department of Electrical and Electronic Engineering (DIEE) of the University of Cagliari, Italy. He has also held academic and visiting positions in several institutions worldwide, including Xidian University (China) and Aix-Marseille University (France). He received a Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, NY, USA in 1992. His research interests include discrete event systems, hybrid systems, networked control systems, Petri nets and failure diagnosis. On these topics he has published extensively, given several talks and managed international and national research projects. He is currently the Editor in Chief of the IFAC journal Nonlinear Analysis: Hybrid Systems and a Senior Editor of the IEEE Trans. on Automatic Control. He is serving as Vice President for Conference Activities of the IEEE Control Systems Society (2000-21). He is a Fellow of the Institute of Electrical and Electronics Engineers and a Fellow of the International Federation of Automatic Control for contributions to discrete event and hybrid systems. He received in 2017 the People's Republic of China Friendship Award.

Scott Moura is an Assistant Professor at the University of California, Berkeley in Civil & Environmental Engineering and Director of eCAL. He received the Ph.D. degree from the University of Michigan in 2011, the M.S. degree from the University of Michigan in 2008, and the B.S. degree from the UC Berkeley, in 2006 - all in Mechanical Engineering. He was a postdoctoral scholar at UC San Diego in the Cymer Center for Control Systems and Dynamics, and a visiting researcher in the Centre Automatique et Systmes at MINES ParisTech in Paris, France. He is a recipient of the O. Hugo Shuck Best Paper Award, Carol D. Soc Distinguished Graduate Student Mentoring Award, Hellman Faculty Fellows Award, UC Presidential Postdoctoral Fellowship, National Science Foundation Graduate Research Fellowship, University of Michigan Distinguished ProQuest Disser- tation Honorable Mention, University of Michigan Rackham Merit Fellowship, and Distinguished Leadership Award. He has received multiple conference best paper awards, as an advisor & student. His research interests include control & estimation theory for PDEs, optimization, machine learning, batteries, electric vehicles, and the smart grid.