ABSTRACT
Electricity production in the US has changed dramatically since 2000, with the percent of electricity produced from gas growing from 16% to 30%, while coal dropped from 52% to 37%. These changes are primarily driven by two technologies used in shale rock formations, directional drilling to create horizontal wells, and hydraulic fracturing to release the gas within the relatively impermeable rock. This presentation will first give a brief operational overview of hydraulic fracturing. Next, challenges that relate to the control of this technology are described. Lastly, two examples are presented, one a theoretical study investigating the potential of model-based feedback control of the hydraulic fracturing process and the other an implementation that highlights the importance of measurements and data uncertainty when designing effective and robust controllers.

BIOGRAPHY: Dr. Jason Dykstra
Dr. Jason Dykstra received his Ph.D. in Mechanical Engineering from the University of Wisconsin – Madison. He is currently the Chief Advisor to the corporate research group, where he is tasked with creating the technology vision of high risk research. He has worked in the automotive, nuclear, steel mill, and heavy equipment industries before joining the oil services company Halliburton upon completion of his doctorate. At Halliburton he has designed control systems for cementing, cryogenic nitrogen pumping, chemical blending, and high pressure fracking equipment along with fault detection and virtual sensing system that are used in over 100 countries every day. Jason has invented several award winning tools that have been installed in wells in South America, the North Sea, and the Middle East. He holds 62 U.S. patents with over 100 patent applications in process, and was awarded the E&P meritorious award for engineering innovation 2012, the OTC spotlight on innovation award 2012, and a finalist in the world oil awards 2013. Jason is currently interested in creating value by distilling control theory to practice in the broad range of products and services Halliburton offers.

BIOGRAPHY: Dr. Karlene A. Hoo
Karlene A. Hoo has a B.S. degree from the Univ. Pennsylvania and M.S. and Ph.D. degrees from the Univ. of Notre Dame. All her degrees are in chemical engineering. Prior to joining academia she was an employee of Exxon Chemical Co. and the DuPont chemical Co. She has experience in research administration at as co Director of an Industrial consortium on Process Control and Optimization, as an Assoc. Dept. Chair, Assoc. Dean of Research in the engineering, and Assoc. Vice President for Research and Acting Vice President for Research at the university level. In 2011-2013, Karlene was a Program Director at the National Science Foundation in the Industrial Innovations and Partnerships in the Engineering Directorate. Currently, Karlene is a tenured full professor of chemical and biological engineering and the Dean of the Graduate School at Montana State University. Her research interests include modeling of complex dynamical systems, control system synthesis, multivariate statistics, and optimization with applications in chemical, petrochemical, and biological processes.

Therapeutic robotics: challenges of controlling physical interaction
Neville Hogan
Massachusetts Institute of Technology (MIT) , USA

ABSTRACT
Robotic technology can: (i) deliver therapy to aid recovery after neurological disease; (ii) replace limb function following amputation; and (iii) provide assistance to restore function. This exciting new frontier of robotic applications requires sensitive but forceful physical interaction with a human, yet physical contact can severely de-stabilize robots. Despite these challenges, clinical evidence shows that robot therapy is both effective and cost-effective. Motorized amputation prostheses present even greater challenges. They must manage physical interaction with objects in the world as well as with the amputee. This presentation will review how machine mimicry of natural control provides the gentleness required for robotic therapy and enables seamless coordination of natural and prosthetic limbs. A pre-requisite for success in these applications is a quantitative knowledge of the human motor control system.

BIOGRAPHY
Neville Hogan is Sun Jae Professor of Mechanical Engineering and Professor of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT). He received the Diploma in Engineering (with distinction) from Dublin Institute of Technology in Ireland, and M.S., Mechanical Engineer and Ph.D. degrees from MIT. Following industrial experience in engineering design, he joined MIT’s faculty in 1979 and has served as Head and Associate Head of the MIT Mechanical Engineering Department’s System Dynamics and Control Division. He is presently Director of the Newman Laboratory for Biomechanics and Human Rehabilitation and a founder and director of Interactive Motion Technologies, Inc. His research interests include robotics, sensory-motor neuroscience, and rehabilitation engineering, emphasizing the control of physical contact and dynamic interaction. He serves on the editorial boards of IEEE Transactions on Neural Systems and Rehabilitation Engineering, the Journal of Motor Behavior and the Journal of Healthcare Engineering. He has been awarded Honorary Doctorates from Delft University of Technology and Dublin Institute of Technology; the Silver Medal of the Royal Academy of Medicine in Ireland; the Henry M. Paynter Outstanding Investigator Award, and the Rufus T. Oldenburger Medal from the Dynamic Systems and Control Division of the American Society of Mechanical Engineers.

Controlling the Next Generation of Bipedal Robots and Robotic Assistive Devices
Aaron Ames (2015 Eckman Award Winner)
Georgia Institute of Technology
 

ABSTRACT
Humans have the ability to walk with deceptive ease, navigating everything from daily environments to uneven and uncertain terrain with efficiency and robustness. With the goal of achieving human-like abilities on robotic systems, this talk presents the process of formally achieving bipedal robotic walking through controller synthesis inspired by human locomotion, and it demonstrates these methods through experimental realization on numerous bipedal robots and robotic assistive devices. Motivated by the hierarchical control present in humans, human-inspired virtual constraints are utilized to synthesize a novel type of control Lyapunov function (CLF); when coupled with hybrid system models of locomotion, this class of CLFs yields provably stable robotic walking. Going beyond explicit feedback control strategies, these CLFs can be used to formulate an optimization-based control methodology that dynamically accounts for torque and contact constraints while being implementable in real-time. This sets the stage for the unification of control objectives with safety-critical constraints through the use of a new class of control barrier functions provably enforcing these constraints. The end result is the generation of bipedal robotic walking that is remarkably human-like and is experimentally realizable, together with a novel control framework for highly dynamic behaviors on bipedal robots. Furthermore, these methods form the basis for achieving a variety of advanced walking behaviors—including multi-domain locomotion, e.g., human-like heel-toe behaviors—and therefore have application to the control of robotic assistive devices, as evidenced by the demonstration of the resulting controllers on multiple robotic walking platforms, humanoid robots and prostheses.

BIOGRAPHY
Aaron D. Ames is an Associate Professor at the Georgia Institute of Technology in the George W. Woodruff School of Mechanical Engineering and the School of Electrical and Computer Engineering as of July 2015. Prior to joining Georgia Tech, he was an Associate Professor and Morris E. Foster Faculty Fellow II in Mechanical Engineering at Texas A&M University, with joint appointments in Electrical & Computer Engineering and Computer Science & Engineering. Dr. Ames received a BS in Mechanical Engineering and a BA in Mathematics from the University of St. Thomas in 2001, and he received a MA in Mathematics and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley in 2006. At UC Berkeley, he was the recipient of the 2005 Leon O. Chua Award for achievement in nonlinear science and the 2006 Bernard Friedman Memorial Prize in Applied Mathematics. Dr. Ames served as a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology from 2006 to 2008. In 2010 he received the NSF CAREER award for his research on bipedal robotic walking and its applications to prosthetic devices. Dr. Ames’ research interests center on robotics, nonlinear control, hybrid systems and cyber-physical systems, with special emphasis on foundational theory and experimental realization on robotic systems. His research lab designs, builds and tests novel bipedal robots and prostheses with the goal of achieving human-like bipedal robotic walking and translating these capabilities to robotic assistive devices.
 

Nano to Really Macro: How working with AFMs can help with design of medical devices for hospitals in resource poor countries
Delphine Dean
Clemson University, USA

ABSTRACT
In this talk, I will describe some of our work on nanomechanics of biological systems and design of medical devices for hospitals in resource poor countries. These may sound like very disparate areas. However, you may be surprised to see how well the skills students learn in one translate well to the other. Atomic Force Microscopy and high precision instrumentation are common tools for the basic sciences. We can use these systems to measure small-scale intermolecular forces and characterize the nano-structures of individual cellular components. These types of measurements help to build more accurate models of tissues and organs to predict behavior during disease and injury. Beyond the basic sciences, the same types of concepts and skills needed for nanoscience work can be applied to solve real-world engineering problems in resource poor hospitals today. Working with engineers and clinicians in Tanzania, our students have designed several novel solutions to problems they have seen in clinics. These range from infant warmers to ink-jet printed diabetes test supplies to basket woven neck braces. In addition, while in the hospitals, our students put their debugging skills to the test by helping to repair and maintain clinical devices and equipment. Experiences in the lab and in the field give students a rounded perspective on engineering and a clearer outlook on their future career paths.

BIOGRAPHY
Dr. Delphine Dean is the Gregg-Graniteville Associate Professor of Bioengineering at Clemson University. She earned her Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2005 and started her faculty position at Clemson in January 2007. Her lab leads a wide range of studies focused on understanding mechanics and interactions of biological systems across length scales. Her expertise is in nano- to micro-scale characterization of biological tissues including experimental techniques such as atomic force microscopy and mathematical modeling such as finite element analysis. She is the recipient of the 2011 Phil and Mary Bradley Award for Mentoring in Creative Inquiry for her work in mentoring undergraduates at Clemson, where she currently mentors 12 undergraduate creative inquiry research and design teams. These multi-year undergraduate project teams have focused on several areas including the redesign of medical training simulators, investigating the use of robotics for solving biomedical problems, and developing medical technology for the resource poor countries. Working with collaborators in country, her students have created new sustainable technological solutions for Tanzanian clinical settings. The teams have been recognized with several awards, including most recently 2014 Lemelson-MIT Undergraduate Cure-It prize.

Mathematical Optimization in Everyday Life: The Growing Role of Hidden Algorithms in Smart Products and Systems
Stephen Boyd
Stanford University, USA

ABSTRACT
Many current products and systems employ sophisticated mathematical algorithms to automatically make complex decisions, or take action, in real-time. Examples include recommendation engines, search engines, spam filters, on-line advertising systems, fraud detection systems, automated trading engines, revenue management systems, supply chain systems, electricity generator scheduling, flight management systems, and advanced engine controls.

I'll cover the basic ideas behind these and other applications, emphasizing the central role of mathematical optimization and the associated areas of machine learning and automatic control. The talk will be nontechnical, but the focus will be on understanding the central issues that come up across many applications, such as the development or learning of mathematical models, the role of uncertainty, the idea of feedback or recourse, and computational complexity.
 

BIOGRAPHY
Stephen Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He received the A.B. degree in Mathematics from Harvard University in 1980, and the Ph.D. in Electrical Engineering and Computer Science from the University of California, Berkeley, in 1985, and then joined the faculty at Stanford. His current research focus is on convex optimization applications in control, signal processing, and circuit design. Professor Boyd is the author of many research articles and three books: Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced several open source tools, including CVX (with Michael Grant), a widely used parser-solver for convex optimization.

Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award, given annually for the greatest contribution to the field of control engineering by someone under the age of 35. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, given every three years for excellence in computational mathematical programming. He is a Fellow of the IEEE and SIAM, a Distinguished Lecturer of the IEEE Control Systems Society, and a member of the National Academy of Engineering. He has been invited to deliver more than 60 plenary and keynote lectures at major conferences in control, optimization, and machine learning.

Featured Opening Plenary Talk and Reception, Tuesday evening, july 5, 6-7 pm, Salon E

ACC 2016 is proud to present a Special Opening Lecture by Jack Little, cofounder and president of MathWorks. The lecture will be immediately followed by the Opening Reception, generously sponsored by MathWorks.

Accelerating the Pace Toward Smarter Controlled Systems
Jack Little, MathWorks, USA
Tuesday, July 5, 6:00 - 7:00 pm
Location: Salon E

Thirty years ago, computer-aided control system design involved an exclusive community of engineers, typically in top research labs or large companies, running esoteric codes on timeshared minicomputers to design and analyze control algorithms, often for expensive systems produced in low volumes. Today, computer-aided control system design has grown into Model-Based Design, encompassing not only system analysis and algorithm design, but also implementation through code generation, plus verification and validation on both models and embedded code. It is used in every industry that creates today’s smart systems – aerospace, automotive, industrial automation, medical devices, robotics, energy, and many more – not only for the controls but integrating computer vision, communication, and machine learning. In this talk, Jack Little reviews the evolution of control design tools, and the corresponding changes in controls education and research. Jack then looks forward to the future of Model-Based Design and how it is addressing the next generation of control engineers: researchers and developers working on challenges such as cyber-physical systems and distributed systems, but also students and makers taking advantage of easy-to-use software with low-cost hardware – everyone building the smarter controlled systems of the future.

Jack Little is president and cofounder of MathWorks. He was a coauthor and principal architect of early versions of the company's flagship MATLAB product as well as Signal Processing Toolbox and Control System Toolbox.  Jack holds a B.S. degree in electrical engineering and computer science from MIT (1978) and an M.S.E.E. degree from Stanford University (1980).  A Fellow of the IEEE and Trustee of the Massachusetts Technology Leadership Council, he writes and speaks about technical computing, Model-Based Design, entrepreneurship, and software industry issues.