Questions can be directed to the Workshop Chair, Prof. Warren Dixon.

Traffic Flow Control via PDE Techniques 
Organizers: Nikolaos Bekiaris-Liberis, Maria Laura Delle Monache, Delphine Bresch-Pietri, Rafael Vazquez  
Time: 9:00 AM - 5:00 PM
Location: Splash 10

Stochastic Control and its Applications: A workshop dedicated to Sean Meyn's 60th birthday  
Organizers: Prabir Barooah, Prashant G. Mehta  
Time: 9:00 AM - 5:00 PM
Location: Splash 1-2

Secure and Resilient Control Systems   
Organizers: Hideaki Ishii, Quanyan Zhu   
Time: 9:00 AM - 5:00 PM
Location: Splash 9

Computation-aware Algorithmic Design for Cyber-Physical Systems    
Organizers: Raphaël M. Jungers, Maria Prandini, Ricardo G. Sanfelice, Majid Zamani   
Time: 9:00 AM - 5:00 PM
Location: Splash 17-18

CANCELLED Sensing, Modeling and Control of Additive Manufacturing Process    
Organizers: Abhijit Chakraborty, Amit Surana, Xu Chen   
Time: 9:00 AM - 5:00 PM
Location: Splash 12

Intersections of Machine Learning and Parameter Estimation in Control     
Organizers: Travis E. Gibson, Joseph Gaudio, Anuradha M. Annaswamy   
Time: 9:00 AM - 5:00 PM
Location: Splash 13-14

Smart Buildings: A Status Quo Check      
Organizers: Rong Su, Christos G. Cassandras   
Time: 9:00 AM - 5:00 PM
Location: Splash 15-16

Learning for Control       
Organizers: Konstantinos Gatsis, Pramod Khargonekar, Manfred Morari, George J. Pappas    
Time: 9:00 AM - 5:00 PM
Location: Splash 11-12

Nonlinear Model Reduction by Moment Matching
Organizers: Giordano Scarciotti, Alessandro Astolfi
Time: 9:00 AM - 1:00 PM
Location: Splash 5-6

Parameter Convergence in Adaptive Control without Persistence of Excitation
Organizers: Sayan Basu Roy, Shubhendu Bhasin, Rushikesh Kamalapurkar
Time: 9:00 AM - 1:00 PM
Location: Splash 7-8

Tools for Distributed and Nonlinear Control of Dynamical Networks
Organizers: Tengfei Liu, Zhong-Ping Jiang 
Time: 1:00 PM - 5:00 PM
Location: Splash 3-4

Traffic Flow Control via PDE Techniques

Workshop overview:

Description: This workshop explores advances in the field of vehicular traffic flow control utilizing PDE techniques. The workshop includes presentations from a diverse group of renowned and pioneer researchers in the field of PDE-based traffic flow control, covering both theoretical and practical aspects. In particular, state-ofthe-art control design methodologies for PDEs are presented, such as, for example, backstepping, Lyapunov-based methods, and methods originally developed for PDE-ODE interconnections, which are applied to traffic, addressing significant traffic flow control problems, such as, for example, mitigation of traffic waves and traffic congestion as well as travel time and fuel consumption minimization. We expect the audience to become acquainted with the state-of-the-art of the methodologies for control and estimation of distributed parameter systems as well as for traffic flow control. We also envision that the workshop is useful in promoting new collaborations, which may pave the way for the future advancements. Our goal is to attract both researchers interested in control of distributed parameter systems as well as researchers interested in control of traffic systems, including researchers from academia (at various seniority levels) and control practitioners from industry.

Organizers: Nikolaos Bekiaris-Liberis, Maria Laura Delle Monache, Delphine Bresch-Pietri, Rafael Vazquez

More info: workshop's website

Stochastic Control and its Applications: A workshop dedicated to Sean Meyn's 60th birthday

Workshop overview:

Description: This workshop is being organized to celebrate Professor Sean Meyn's 60th birthday and honor his multiple long-lasting contributions in stochastic systems, Markov processes, networks, and control theory. This workshop brings together 13 of his colleagues who will present a broad range of contemporary topics in different areas of systems and control theory. One other main goal of this workshop is to inspire a future generation of researchers in this vibrant field.

Organizers: Prabir Barooah, Prashant G. Mehta

More info: workshop's website

Secure and Resilient Control Systems 

Workshop overview:

Description: Modern control systems are characterized by tight integration of cyber (computation and communication) components with physical systems. This paradigm is expected to transform critical sectors of society including energy, health care, and transportation. The integration of cyber systems, however, creates new entry points for cyber attacks, which degrade the availability of the physical system, disrupt the communication protocols needed for coordinated control, and compromise the safety and performance of physical components. Security of control systems poses an inherently multi-disciplinary research challenge. Network and systems security is needed to discover possible cyber vulnerabilities and develop secure protocols. The incentives, capabilities, and goals of adversary must be understood and modeled, through techniques including game theory. The control actions should be robust to the impact of possible attacks and enable recovery of system functionality when attacks do occur. The proposed workshop will present a holistic view of control system security, with perspectives on network security, game theory, and control, as well as a view for how these disciplines can be combined to design resilient, safe, and secure control systems. From the application side, we will place a particular emphasis on the security of power systems, which is one of the most active research domains in this area. Case studies on different control and regulation operations in energy management systems as well as the development of testbeds for the cyber-physical security of such systems will be presented. We plan to have nine presentations given by experts who have recently worked on the subject with different backgrounds including control theory, game theory, and power systems. We also intend to include a short session by a representative of NSF who will provide a perspective from the funding agency on security related issues.

Organizers: Hideaki Ishii, Quanyan Zhu

More info: workshop's website

Computation-aware Algorithmic Design for Cyber-Physical Systems

Workshop overview:

Description: We propose a one-day workshop to highlight recent advances and developments in the field of cyber-physical systems (CPS) with a specific focus on the need of accounting for computation constraints in algorithm design, also dictated by the communication structure of the system. To this purpose, we bring together outstanding researchers from leading institutions and industries worldwide. The target audience comprises graduate level control theorists, computer scientists and engineers, as well as researchers with a strong interest in CPS verification and control, either from a theoretical or an application perspective.

Organizers: Raphaël M. Jungers, Maria Prandini, Ricardo G. Sanfelice, Majid Zamani 

More info: workshop's website

CANCELLED Sensing, Modeling and Control of Additive Manufacturing Process    

Workshop overview:

Description: Recent years have seen an increase in an industrial push to mature additive manufacturing technology from research to production ready stage. Widespread adoption of the additive manufacturing technology is challenged by lack of quality assurance arising from part-to-part repeatability and machine-to-machine variability. This is a major concern for safety-critical applications where component failures cannot be tolerated. The AM community is expressing that qualification and certification are the “long poles in the tent”. Numerous government agencies, such as NAVY, NIST in their AM roadmap have identified multiple factors that are linked to an accelerated qualification process and “computationally guided processes and closed loop process controls” have always emerged as the potential leading factor which could aid in accelerated qualification of AM process and components. Consequently, academic researchers are working on demonstrating the capability of in-situ monitoring and closed-loop controls in the AM process. However, some significant gaps still exist from in-situ monitoring and control perspective to push the AM technology from research to industrialization. The objective of this workshop is to explore and discuss how this gap can be bridged. The workshop will focus on the particular themes: (a) Reliable in-situ monitoring technique: Often time the reliability of the in-situ monitoring algorithm is overlooked in literature making the technique less attractive for industry to adopt. The goal will be to explore techniques that have the intent of industrialization. (b) Control architecture framework and techniques: In-situ control literature is not as rich as monitoring. The fundamental question of an appropriate control architecture framework(s) taking advantage of the multiple time and length scales in the AM process will be the main focus. (c) Open access machines: One of the challenges in deploying any in-situ monitoring and control techniques on a production ready machine is the "black-box" nature of the machine. The focus will be to understand how these open machines can be effective in enabling part qualification.

Organizers: Abhijit Chakraborty, Amit Surana, Xu Chen

More info: workshop's website, and workshop's one-pager (with agenda)

Intersections of Machine Learning and Parameter Estimation in Control

Workshop overview:

Description: The focus of this workshop is the analytical foundations of Machine Learning (ML) algorithms and their intersection with parameter estimation in control. By machine learning we mean the use of statistical techniques to enable computer systems to "learn" using data, typically using offline training methods. Starting from a functional approximation perspective, this learning corresponds to iterative adjustments of parameters of the approximation function, frequently based on a gradient descent approach, with the adjustments carried out so as to minimize an underlying cost function. Control systems, on the other hand, focus on methods for automated regulation and tracking in engineering systems, with guidelines for providing guarantees of stability, robustness and convergence in the presence of various uncertainties. Off-line and on-line learning of the underlying control parameters have been analyzed extensively, over the past four to five decades, in sub-disciplines in control such as system identification and adaptive control. It is in these sub-disciplines whereby parameter estimation occurs, either implicitly or explicitly, and thus an obvious intersection with ML arises. In fact, when one writes down the dynamics of Stochastic Gradient Descent (SGD), the control gain update law in adaptive control, or the MAP parameter estimate in regression (Bayesian or otherwise), the three sets of equations are basically identical in structure. Interesting and rather subtle differences do exist however. Another area of intersection between the two fields arises when one treats SGD explicitly as a dynamical system and leverages the broad array of tools in control theory to study its robustness properties. The goal of this workshop is to understand the aforementioned intersections between ML and control systems. The two major thrusts of this workshop are (1) methods for combining the analytical rigor in control systems with the representational power of ML algorithms, (2) parameter update laws combining features and analysis from control and accelerated methods.

Organizers: Travis E. Gibson, Joseph Gaudio, Anuradha M. Annaswamy

More info: workshop's website

Smart Buildings: A Status Quo Check

Workshop overview:

Description: A smart building is a structure that uses automated processes to control the building's operations including heating, ventilation, air conditioning, lighting, security and other systems. A smart building uses sensors, actuators and microchips, in order to collect data and manage it according to prescribed functions and services. This infrastructure helps owners, operators and facility managers improve asset reliability and performance, which reduces energy use, optimizes how space is used and minimizes the environmental impact of buildings. Making a smart building, or making a building smart, begins by linking core systems such as lighting, power meters, water meters, pumps, heating, fire alarms and chiller plants with sensors and control systems. The key feature of a smart building is "integration". In this workshop several active researchers in this field will report their recent technical progresses at both individual and program levels on smart buildings, and some visionary discussions on the roles of IoT and data analytics, aiming to showcase some recent achievements and at the same time identify challenges ahead in order to arouse more interests and efforts at a broader societal level to ensure research sustainability.

Organizers: Rong Su, Christos G. Cassandras

More info: workshop's website

Learning for Control

Workshop overview:

Description: Over the past two decades, computing and communications have resulted in the creation, transmission and storage of data from all sectors of society. Over the next decade, the biggest generator of data is expected to be IoT devices which sense and control the physical world. This explosion of data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. As control theory has been firmly rooted in tradition of model-based design, the availability and scale of data (both temporal and spatial) will require rethinking of the foundations of our discipline. There is a wonderful opportunity to advance both the theory of control systems in a more data driven fashion as well as have impact outside our discipline. Furthermore, the case for broader impact, industrial or societal is incredible.

Organizers: Konstantinos Gatsis, Pramod Khargonekar, Manfred Morari, George J. Pappas

More info: workshop's website

Nonlinear Model Reduction by Moment Matching

Workshop overview:

Description: The availability of mathematical models is essential for the analysis, control and design of modern technological devices. As the computational power has advanced, the complexity of these mathematical descriptions has increased. This has maintained the computational needs at the top or above the available possibilities. A solution to this problem is represented by the use of reduced order models, which are exploited in the prediction, analysis and control of a wide class of behaviors. For instance, reduced order models are used to simulate weather forecast models and design very large scale integrated circuits and networked dynamical systems. The model reduction problem can be informally formulated as the problem of finding a simplified description of a dynamical system in specific operating conditions, preserving at the same time specific properties, e.g. stability. For linear systems, the problem has been addressed from several perspectives which can be divided into two main groups: singular value decomposition approximation methods and Krylov approximation methods. The theory of balanced realizations, the use of Hankel operators and of proper orthogonal decomposition belong to the first group, whereas the use of interpolation theory belongs to the latter. The additional difficulties of the reduction of nonlinear systems carry the need to develop different or “enhanced” techniques. Several methods which extend balancing and proper orthogonal decomposition to nonlinear systems have been proposed. Reduction of special classes of nonlinear systems and local reduction (for instance around a limit cycle) represent another approach. Although many results and efforts have been made, at present there is no complete theory of model reduction for nonlinear systems or, at least, not as complete as the theory developed for linear systems. The proposed workshop is intended to give an overview on the main developments in nonlinear model reduction by moment matching obtained in recent years. The workshop is intended as a morning half-day workshop.

Organizers and speakers: Giordano Scarciotti, Alessandro Astolfi

Parameter Convergence in Adaptive Control without Persistence of Excitation

Workshop overview:

Description: This workshop is aimed at providing a comprehensive understanding of recent adaptive control algorithms with a special focus on parameter convergence and transient performance improvement. Classical adaptive controllers typically guarantee closed-loop system stability and asymptotic convergence of tracking error, however, parameter convergence is only guaranteed if a stringent condition of persistence of excitation (PE) is satisfied by the regressor signal. Some recent contributions in adaptive control, like concurrent learning (CL), integral concurrent learning (ICL), Initial Excitation (IE)-based adaptive control, have shown that parameter convergence is possible without requiring the restrictive PE condition, rather milder conditions like a full-rank condition on past stored data along systems trajectory (in CL-based framework) or the condition of initial excitation (in IE-based framework) can suffice for parameter convergence, and thereby improve transient response by ensuring exponential stability. The workshop would cover crucial details of these recent developments for relaxing the PE condition for parameter convergence in adaptive control.

Organizers and speakers: Sayan Basu Roy, Shubhendu Bhasin, Rushikesh Kamalapurkar

More info: workshop's website

Tools for Distributed and Nonlinear Control of Dynamical Networks

Workshop overview:

Description: To date, the research has reached the stage that emphasizes developing methodologies that can handle the complexity characterized by uncertainty, nonlinearity, time-varying dynamics, delays and interconnections. The seamless integration of controls, communication and computation results in deeply and dynamically intertwined "cyber" and physical processes, and has been enabling many new applications in robotic systems, electric smart grids, chemical processes, biological systems, smart manufacturing, intelligent transportation systems, etc. Nonlinearity is ubiquitous in nature. For such dynamic networks, the current nonlinear control theory is insufficient to addressing the design challenges and the related engineering application problems. Solving the new problems will be of special interest for the control of various practical systems, and will even enrich the control theory. This workshop aims to report the new research results, made by leading researchers, that address some of the new emerging theoretical problems with nonlinear and distributed control, as well as their applications to practical systems.

Organizers and speakers: Zhong-Ping Jiang, Miroslav Krstic, Karl Henrik Johansson, and Tengfei Liu

More info: workshop's website