WORKSHOPS

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SYNOPSIS:
Every nation’s energy savings goals contribute toward greater energy independence and a cleaner environment. In this context, improving the energy efficiency of new and existing buildings will have a significant contribution to this strategic goal of reducing national energy demand. While design of energy efficient building solutions, e.g., net-zero or net-positive energy buildings, will become the new state-of-the-art in commercial and residential architecture, for existing buildings, it is analyzing, selecting and implementing cost-effective retrofit solutions that have the largest impact on energy use.
Traditionally, building Heating, Ventilation and Air-Conditioning (HVAC) equipment and building management systems have been selected and installed in an-ad hoc fashion based on domain expertise. In a similar manner, control for building and HVAC systems has been implemented with the sole objective of satisfying the occupancy comfort. As a consequence, the present day building thermal comfort is satisfied at significantly lower efficiency compared to the new building designs that incorporate the most recent art in energy efficient technologies.
In order to achieve lower energy goals, in recent years, analysis, optimization and control methods developed in the systems theory and control engineering field have become pervasive and lead to a paradigm shift in the domain of HVAC system design and control. The results of these efforts have revealed that the potential for energy savings can be unleashed by systematic investigation of building systems supported by modeling, analysis and control architecture design.
This workshop aims to bring together researchers in the area of building systems and HVAC control to present the results of their work in a tutorial fashion to the control community. The goal of the workshop is to present a clear and concise picture of the technological landscape of present enabling technologies for control architecture retrofit and design of energy efficient buildings.

The workshop will include discussion of:
* Building and HVAC modeling, model calibration, model reduction, load estimation
* Control architecture design and model based predictive control for building and HVAC control
* Impact of model estimation error on closed-loop performance


Keywords: energy-efficiency; heating, ventilation and air-conditioning; HVAC; modeling, control

About the speakers:
Sunil Ahuja is a Senior Research Scientist at United Technologies Research Center, East Hartford, CT, USA. He received his Ph.D. in Mechanical Engineering from Princeton University in 2009, where he was awarded the Ray Grimm Memorial Prize in Computational Physics in recognition of his contributions to computational physics. Dr. Ahuja has industrial experience in modeling, control, and diagnostics of high-performance buildings, and his areas of expertise include high-performance computing, model reduction, dynamical systems, control, numerical analysis, and geometric mechanics. He is a member of SIAM, IEEE, AIAA and APS.
Veronica Adetola is a research scientist at United Technologies Research Center in East Hartford, Connecticut. She obtained her B.Sc. degree in Chemical Engineering from Obafemi Awolowo University, Nigeria, in 1999. She then worked as a process engineer for two years. She received the M.Sc. and Ph.D. degree in Chemical Engineering from Queen's University, Canada. In 2011 she received Best Methodology/Theory Paper published in the IFAC Journal of Process Control over the past three years from the International Federation of Automatic Control (IFAC). Her current research interests include nonlinear adaptive control, real-time optimization and model predictive control.
Draguna Vrabie is a research scientist at United Technologies Research Center in East Hartford, Connecticut. She graduated from University of Texas at Arlington with a Ph.D. in Electrical Engineering. She received her B.Sc. and M.Sc. in Automatic Control and Computer Engineering from "Gh. Asachi" Technical University Iasi, Romania. Prior to joining UTRC she was a research associate at the Automation & Robotics Research Institute in Fort Worth, Texas. She received the Best Paper Award at the International Joint Conference on Neural Networks (IJCNN’10). Dr. Vrabie serves as associate editor for IEEE Trans. Neural Networks, and U.K. Trans. Inst. Measurement & Control.

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SYNOPSIS: Systems and synthetic biology have been forecasted several times among the major fields of science and technology of the twenty-first century. Indeed, systems and synthetic biology attempt to link the methodologies developed in the analysis and design of dynamical systems to the study and synthesis of biological systems. This workshop aims to present recent results in systems and synthetic biology, in particular concerning genetic regulatory networks and gene circuits. A concise overview of these areas that highlights major concepts and issues will be also provided in the workshop.

The tentative titles and corresponding speakers of the talks in the proposed workshop are as follows:

1. 1. "Equilibria and Stability Investigation in Genetic Regulatory Networks",
       by Graziano Chesi, University of Hong Kong
2. 2. "Optimization of Synthetic Genetic Oscillators",
       by Chun-Liang Lin, National Chung Hsing University
3. 3. "Robustness Analysis in Uncertain Genetic Regulatory Networks",
       by Graziano Chesi, University of Hong Kong
4. 4. "Design of Synthetic Biological Logic Circuits",
       by Chun-Liang Lin, National Chung Hsing University

The first talk describes recent results on the computation of the equilibria and on the analysis of the major stability properties of genetic regulatory networks.
The second talk deals with the design problem of synthetic biological oscillators, in particular concerning their optimization through genetic algorithms.
The third talk addresses the analysis of fundamental robustness indexes of genetic regulatory networks whose mathematical models are affected by structured parametric uncertainty.
Lastly, the fourth talk considers the synthesis of biochemical logic gates based on enzymatic reactions.

About the speakers:

Graziano Chesi received the Laurea in Information Engineering from the University of Florence in 1997 and the Ph.D. in Systems Engineering from the University of Bologna in 2001. He was with the Department of Information Engineering of the University of Siena during 2000-2006 and then he joined the Department of Electrical and Electronic Engineering of the University of Hong Kong. He was a visiting scientist at the Department of Engineering of the University of Cambridge during 1999-2000 and at the Department of Information Physics and Computing of the University of Tokyo during 2001-2004. Dr. Chesi has served as Associate Editor for Automatica, BMC Research Notes, the European Journal of Control, the IEEE Transactions on Automatic Control, and Systems & Control Letters. Also, he has served as Guest Editor of the Special Issues on Positive Polynomials in Control of the IEEE Transactions on Automatic Control, Systems Biology of the International Journal of Robust and Nonlinear Control, and Visual Servoing of Mechatronics. Dr. Chesi is the Founder and Chair of the Technical Committee on Systems with Uncertainty of the IEEE Control Systems Society. He is author of the book ”Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems” (Springer, 2009), editor of the book ”Visual Servoing via Advanced Numerical Methods” (Springer, 2010), and author of the book ”Domain of Attraction: Analysis and Control via SOS Programming” (Springer, 2011). He is first author in more than 100 publications.
Chun-Liang Lin was born in Tainan, Taiwan, in 1958. He received the Ph.D. degree in aeronautical and astronautical engineering from the National Cheng Kung University, Tainan, in 1991. He was Associate Professor and Professor with the Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, from 1995 to 2003. He is currently Chair Professor with the Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan. Dr. Lin is a Fellow of the Institute of Engineering and Technology and a Fellow of the Chinese Automatic Control Society. He is Associate Editor of the Asian Journal of Control, International Journal of Fuzzy Systems and IEEE Computational Intelligence Magazine. Dr. Lin also serves as the Chair of the IEEE Control Systems Society, Taipei Chapter since 2009. He received the Distinguished Research Award from the National Science Council of Taiwan in 2000, 2003 and 2010, respectively. His research interests include guidance and control, intelligent control, and robust control.

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SYNOPSIS:
At the workshop we present a number of key results and applications for two important tools of system analysis and design: Randomization and Averaging. Both tools allow to avoid many difficulties arising in theory and practice when one tries to analyze or control of "complex" systems. In practical applications traditionally efficient deterministic methods often fail to yield a result when the system is complex. Many of adaptive control or system analysis problems at real time environment have restricted resources and insufficient amount of data available. Unique feature of this workshop is that its material is based upon two books published in Russian and, therefore almost not known at the West: "Randomized Algorithms of Estimation and Optimization Under Almost Arbitrary Noise" by Oleg Granichin and Boris Polyak (Moscow: Nauka, 2003) and "Applied Theory of Discrete Adaptive Control Systems" by Dmitry Derevitskii and Alexander Fradkov (Moscow: Nauka, 1981). The workshop would allow to anyone interested in analysis and design of complex stochastic systems to learn about some new theoretical tools and their application examples.

Workshop Outline:

1. 1. Continuous models building (45 min)
2. 1. a. Averaging for independent disturbances
   2. b. Averaging for dependent disturbances
   3. c. Stochastic continuous model
3. 2. Continuous models justification (45 min)
4. 1. a. Proximity bounds over a finite time interval
   2. b. Proximity bounds over an infinite time interval
   3. c. Conservation of stability
5. 3. Continuous models applications (45 min)
6. 1. a. Analysis of stochastic approximation and adaptation algorithms
   2. b. Analysis of optimization algorithms
   3. c. Analysis and design of nonlinear and adaptive control systems
7. (break 15 min)
8. 4. Randomized Algorithms (45 min)
9. 1. a. Enrichment of the observations' data
   2. b. Example of signal detecting under arbitrary external noise
   3. c. Randomized scenario approach
10. 5. Simultaneous Perturbation Stochastic Approximation (45 min)
11. 1. a. Mean-risk multi-dimensional optimization problems
    2. b. One and Two measurements forms of SPSA
    3. c. Best features of SPSA
12. 6. Compressive Sensing (45 min)
13. 1. a. Coding/Decoding algorithms, spars signals
    2. b. Restricted isometry property and l1-recovery algorithm
    3. c. Random universal measurement operators (matrices)

About the speakers:
Oleg Granichin is a professor of Computer Science Department at Mathematics and Mechanics Faculty of St. Petersburg State University. His research interests include multi-agent adaptive control, compressive sensing, clustering (data mining), nanotechnology, scientific and engineering computing, general theory of computations, adaptive and iterative control, randomized algorithms of stochastic multidimensional estimation and optimization, system identification, control relevant system identification, learning theory, pattern recognition, etc. He received his PhD Degrees from the Leningrad State University (1985) and IPC RAS in Moscow (2001). Oleg Granichin is member of St. Petersburg Mathematical Society, IEEE Control System Society, AMS (American Mathematical Society), Academy of Educational Informatization (Russian). Oleg is the head of the Editorial Board of the Journal "Stochastic Optimization in Informatics". He is an author of several books and student books, and he has published more then 50 papers in peer reviewed scientific journals and more than 70 articles the Conference proceedings.
Alexander Fradkov, b.1948, St.Petersburg, Russia, Diploma degree in mathematics, St.Petersburg State University, (1971), Cand. Sci. degree (1975), Dr.Sc., degree in control engineering, St.Petersburg Electrotechnical Institute (1986). Since 1990 he is Head of Laboratory "Control of Complex Systems", Institute of Problems in Mechanical Engineering of Russian Academy of Sciences, St.Petersburg. Coauthor of 540 papers, 16 books, ten patents. Research interests: nonlinear and adaptive control, control of oscillatory and chaotic systems in mechanics, cybernetical physics. Vice-President of St. Petersburg Informatics and Control Society, member of Russian National Committee of Automatic Control, President of the International Physics and Control Society, member of IEEE CSS Conference Editorial Board in 1998-2011, IEEE Fellow since 2004.


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SYNOPSIS: Autonomous systems and unmanned aerial vehicles (UAVs), can play an important role in many applications including disaster management, and the monitoring and measurement of events. Currently, many missions cannot be accomplished or imply a high level of risk for the people involved, e.g. pilots and drivers, as unmanned vehicles are not available or not permitted. This also applies to search and rescue missions, particularly in bad weather conditions, where pilots need to risk their lives. These missions could be performed or facilitated by using autonomous helicopters with accurate positioning, the ability to land on mobile platforms, such as ship decks, as well as the ability to cooperate with other UAVs and manned aircrafts. Additionally, on a more generic basis, the safe cooperation, coordination and traffic control of multiple entities is a relevant consideration in applications such as automation of industrial warehousing, surveillance by means of aerial and ground vehicles, and transportation systems. The workshop will be devoted to the accurate common motion estimation and control methods and technologies in order to reach levels of reliability and safety to facilitate unmanned vehicle deployment in a broad range of applications.

Keywords: Autonomous systems; distributed estimation and control techniques, UAV, automated warehousing, aerial surveillance

The workshop will include the following talks:

1. 1. New state estimation/prediction methods for very accurate coupled motion control and large scale system composed of many mobile entities,
   
2. 2. New state estimation/prediction methods for large scale system composed of many mobile entities,
   
3. 3. Simultaneous Localization and Mapping Techniques using the radio signals present in the networked devices,
   
4. 4. Cooperation techniques for intelligent estimation strategies, (Active Sensing)
   
5. 5. Real-time new optimization techniques for scalable and dynamic multi-vehicle route and trajectory planning.
   

Benefits to attendees of this workshop:

1. 1. Acquisition of knowledge about actual problems and possible solutions related to estimation and control of safe wireless high mobility cooperative industrial systems,
2. 2. Discussion about potential applications:
3. 1. a. Autonomous landing of both fixed and rotary-wing UAVs on a moving platform,
   2. b. Vehicle deployment from manned helicopters,
   3. c. Tracking of many high mobility vehicles,
   4. d. Dynamic routing in large-scale warehousing with robustness to conflicts and deadlocks.

About the organizer:
Anibal Ollero is a Scientific Director of FADA-CATEC. Professor at the Universities of Sevilla, Santiago and Malaga, researcher at CNRS (France) and Carnegie Mellon University (USA). He led or participated in more than 110 R&D projects, being in the last years coordinator of FP6 AWARE and scientific and technical coordinator of FP5 COMETS. Author in about 400 publications, including 6 books and about 90 papers in SCI Journals. He obtained 12 awards for his R&D activities including the second EUROP-EURON 2010 technology transfer award and the Javier Benjumea award by Scientific Excellence and Social Impact.

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