H-infinity optimal control is considered one of most significant developments in control theory, and Pramod P. Khargonekar played a key role in developing its potential for robust control of critical processes in industries ranging from aerospace and automotive to processing and manufacturing. He realized that a new fundamental theory based on state-space representations was feasible and could provide engineers with a powerful, usable, computational framework for multivariable robust control synthesis compared to hard-to-implement methods based on transfer function theory. This would become known as the Doyle-Glover-Khargonekar-Francis (DGKF) method. He also helped introduce the benefits of multivariable control theory to semiconductor manufacturing, and his work on control algorithms and architectures for the power grid operations is aiding the development of smart grids with larger integration of renewable energy sources.
An IEEE Fellow, Khargonekar is a Distinguished Professor and Vice Chancellor for Research with the University of California, Irvine, CA, USA.
A leader in the effort to optimize and control large-scale dynamic and distributed systems, John N. Tsitsiklis’ algorithmic innovations have made possible advances in diverse applications ranging from dynamic resource allocation to sensor networks and distributed computation. Dynamic programming, the central methodology behind sequential decision making and control, often suffers from the curse of dimensionality. Tsitsiklis’ work is behind some of the most powerful methods for overcoming this challenge in settings such as reinforcement learning, path planning, and the pricing of complex financial derivatives. Furthermore, his early work on consensus algorithms and distributed and asynchronous computation is impacting modern large-scale optimization methods, network management, and distributed control.
An IEEE Fellow and a member of the National Academy of Engineering, Tsitsiklis is a Clarence J. Lebel Professor of Electrical Engineering at the Massachusetts Institute of Technology, Cambridge, MA, USA.
Richard M. Murray’s efforts in applying control techniques to improve engineering and industrial processes are impacting applications including autonomous vehicles, networked control systems, and synthetic biology. Murray’s work in autonomous vehicles include advances in nonlinear control theory that exploit geometric structure for real-time trajectory generation and tracking, as well as analysis and design of cooperative and consensus-based control systems for networked, multiagent systems. Murray’s contributions to molecular and synthetic biology include identification, modeling, and design techniques to allow bioengineers to analyze and synthesize biological pathways and circuits inside living cells. Murray’s group has also developed computationally tractable approaches for synthesis of reactive control protocols applicable to control systems in which the decision-making logic satisfies safety, fairness, and reactivity constraints.
An IEEE Fellow, Murray is the Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering at the California Institute of Technology, Pasadena, CA, USA.
Arthur J. Krener’s foundational work on nonlinear control provided the definitive treatment on controllability and observability of time-variant, real-world systems and has spurred tremendous progress in the development of nonlinear control theory. Krener’s work during the 1970s set the cornerstone for control of nonlinear systems and the resulting research paper was selected by the IEEE Control Systems Society as one the 25 Seminal Papers of the 20th Century for its far-reaching importance. Krener’s work on a bifurcation-based approach to controlling models of rotating stall and surge has been invaluable to the U.S. Air Force’s study of jet engine instabilities. He has also been a leader in developing software tools for implementing the latest methods of nonlinear control.
An IEEE Life Fellow, Krener is a research professor with the Department of Applied Mathematics at the Naval Postgraduate School, Monterey, CA, USA.
A giant in the control systems field, Bruce A. Francis helped grow and popularize the concept of H-infinity optimal control, which is perhaps the most important development in control theory of the past 30 years. His work on the internal model principle has provided one of the most fundamental results in linear-multivariable control and has become an indispensable principle for design of today’s control systems. Prof. Francis also pioneered the development of robust control for sampled-data systems, which has important implications in signal processing for connecting digital systems with analog systems. Many of the most widely used computer-aided control system design tools are based on Prof. Francis’ contributions, impacting industries such as aerospace, automotive, manufacturing, robotics, and chemical processing.
An IEEE Life Fellow, Dr. Francis is an Emeritus Professor with the University of Toronto, Ontario, Canada.
Tamer Ba?ar has made fundamental contributions to the field of decision and control for over 40 years. He has led the way in establishing a comprehensive theory for dynamic games, which has helped the decision and control field grow from addressing single-criterion problems to frameworks with multiple criteria and complex information structures. This work has had renewed applicability to wireless communication networks, Internet data structure and routing, and network security. Dr. Ba?ar has also pioneered the game-theoretic approach to robust estimation and control, which has had significant impact in other fields as well, such as economics. Through his work in hierarchical decision-making, he has revolutionized the way dynamic multilevel optimization problems are solved.
An IEEE Life Fellow, Dr. Ba?ar is the Swanlund Endowed Chair and CAS Professor of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign, IL, USA.
Stephen P. Boyd’s vision that convex optimization methods can transform the theory and practice of control system analysis and design has led to one of the most important developments in the field over the last 25 years. Working with other researchers, Boyd developed a new style of research in control that combines advanced mathematical concepts with effective numerical computation, using a formal reduction process of a control problem to a convex optimization problem. Convex optimization problems are readily and reliably solved numerically, so the reduction gives a theoretical and practical solution of the original problem. No one is considered to have done more to articulate, develop, systematize, advance, and popularize the role of convex optimization than Dr. Boyd. He has helped to developed many of the basic computational techniques, showed how to apply them to problems in systems and control, and illuminated the powerful connections to essential concepts in other disciplines, such as computational mathematics, statistics, machine learning, finance, circuit design, networking, and signal processing.
An IEEE Fellow, Dr. Boyd is the Samsung Professor of Electrical Engineering at Stanford University, Palo Alto, CA, USA.
Alberto Isidori’s groundbreaking work has changed the way the control systems community thinks about nonlinear control and has helped shape the field. Dr. Isidori’s research in the early 1970s focused on systems realization, resulting in the first complete theory of minimal realization for a class of nonlinear systems. He then extended the geometric theory used for feedback design in multivariable linear systems to general classes of nonlinear systems. This work is considered a milestone in the study of nonlinear feedback systems. Dr. Isidori also developed the concept of nonlinear zero dynamics, which has had fundamental impact on designing feedback laws for nonlinear systems. His contributions to regulation and tracking in nonlinear systems resulted in the design of a feedback law that solves the nonlinear equivalent of the servomechanism problem in linear control. Dr. Isidori’s Nonlinear Control Systems (Springer Verlag, 3rd ed. 1995) is considered the definitive treatment of nonlinear control systems and has had lasting impact.
An IEEE Life Fellow, Prof. Isidori is currently a professor of systems and control with Sapienza University of Rome, Italy.
Eduardo D. Sontag’s contributions to nonlinear feedback for control and signaling systems opened the floodgates to creativity in nonlinear designs, benefiting a wide range of engineering disciplines. Dr. Sontag’s control Lyapunov function (CLF), input-to-state stability (ISS), and related concepts help in the design of stable nonlinear feedback systems. Dr. Sontag presented the CLF concept in 1989 and it quickly pervaded the control literature. CLF provides control practitioners with the ability to make appropriate feedback control choices. Also in 1989, Dr. Sontag’s ISS concept helped tackle the difficulties presented by uncertainty in nonlinear systems. With ISS, he showed how to capture the effect of persistent disturbances in nonlinear systems, which has enabled engineers to solve many robust stabilization problems.
An IEEE Fellow, Dr. Sontag is a professor with the Department of Mathematics at Rutgers University, Piscataway, N.J., where he is also in the graduate faculty of the Computer Science and the Electrical and Computer Engineering Departments.
Graham C. Goodwin has made a lastingimpact on both the theory and real-world industrial applications of control systems science. Dr. Goodwin and his colleagues were one of the first to produce a rigorous proof of convergence of discrete-time deterministic and stochastic adaptive control algorithms. The paper detailing this breakthrough was named one of the 25 most influential papers of the 20thcentury on control. In the area of digital control, Dr. Goodwin was the first to recognize that the “Z-Transform” was inappropriate for high-speed sampling, and developed what was named the “delta operator.” He demonstrated that there were significant numerical advantages to working with increments rather than absolute measurements. This line of research has many ramifications in practical aspects of signal processing and control.
An IEEE Fellow, Dr. Goodwin is currently a Laureate Professor and Director of the Australian Research Council Centre of Excellence for Complex Dynamic Systems and Control at the University of Newcastle, Australia.
David Quinn Mayne?s wide collection of research contributions has had tremendous impact on the development of control theory. Among these, the most important is his work in optimizing model predictive control (MPC), in which he provided a rigorous mathematical basis for analyzing MPC algorithms. His framework for studying the stability of MPC loops has become highly influential in MPC, whose impact can be seen in today?s high-speed electromechanical, aerospace and automotive systems.
Dr. Mayne was the first to describe what is now known as ?particle filtering,? which is one of the central building blocks in nonlinear filtering. These methods are used in a vast array of applications including vehicle autopilots, aircraft tracking and the prediction of commodity prices. He also introduced the concept of differential dynamic programming as a method for solving optimal control problems and provided early guidelines for adaptive control.
An IEEE Life Fellow, Dr. Mayne is currently an emeritus professor and senior research investigator at Imperial College London.
Mathukumalli Vidyasagar?s groundbreaking work addressing control system theory, paired with his ability to present complex ideas in a clear, concise manner, have helped establish him as a pioneer in the research community. Dr. Vidyasagar designed the method of stable factorization, a fundamental tool in the problem of robust stabilization. He began his career as a professor, spending two decades in academia before being recruited by India?s Department of Defence to create a new R&D institute. Following his work in the government sector, Dr. Vidyasagar joined Tata Consultancy Services, India?s largest information technology services company, where he has built a leading industrial research and development group. A Fellow of the IEEE, he also holds fellowships with the Indian Academy of Sciences, the Indian National Science Academy and the Third World Academy of Sciences. During his career, Dr. Vidyasagar has received several awards, including the 2000 Bode Lecture Prize from the IEEE and the Distinguished Service Citation from the University of Wisconsin.
Lennart Ljung, professor of electrical engineering at the Linköping University in Linköping, Sweden, is a recognized leader in the area of systems and control research whose contributions have had lasting impact over nearly 35 years.
His book, “System Identification—Theory for the User,” is considered a standard reference source, and his career-defining “System Identification Toolbox” for Matlab, a high-level interactive software package for model estimation has been heralded as both a great scientific and commercial success, with many of its principles having been applied to engineering problems for industry world-wide. In his groundbreaking1977 paper, “Analysis of Recursive Stochastic Algorithms,” Dr. Ljung defined a method of proving the convergence of stochastic algorithms that provided a highly effective method for their future analysis.
An IEEE Fellow with Bachelor of Arts, Master of Science and doctoral degrees all from Lund University and the Lund Institute of Technology in Lund Sweden, he has received numerous honorary degrees and awards from institutions around the world.
Dr. P.R. Kumar, Franklin W. Woeltge Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, has made groundbreaking contributions that have helped to shape industrial practice and research in both semiconductor manufacturing and wireless networking.
In his early work, Dr. Kumar developed self-optimizing controllers for systems modeled as Markov chains, which are commonly used as models in engineering and industrial applications. He also analyzed controllers proposed for linear stochastic systems, and established that under certain conditions the estimated parameters would converge and self-tune to an optimal controller.
In the 1980s, he began studying manufacturing systems and advocated a dynamic systems viewpoint to address the problem of scheduling large manufacturing systems. His approach emphasized stability to guarantee that production would stay apace with demand. This led to his development of distributed real-time scheduling policies for complex semiconductor wafer fabricating plants. These policies, designed to reduce mean queuing time and cycle time standard deviation, have since been implemented in industry. His work also led to a wave of interest in the field of queuing networks, focused on studying their stability and performance properties and their control.
In the late 1990s, Dr. Kumar turned to the then emerging field of wireless networking and addressed the fundamental issue of how much traffic such networks could carry and what should be the architecture of their organization. He established a square-root scaling law governing the limit to information transfer in wireless networks, a work that led to a major reassessment of their capabilities. He also developed a network information theory applicable to any wireless network with an arbitrary number of nodes. He further studied the design of protocols for power control, routing and medium access control, and the problem of cross-layer design for wireless networks.
Since 2000, Dr. Kumar has studied the problem of in-network computation in sensor networks, which sheds light on how information should be processed inside sensor networks, and the problem of time-driven computation. He has also addressed the problem of software architecture for a third generation of control systems - networked embedded control systems - that arise from the convergence of control, communication and computation.
He has a bachelor of technology degree in electrical engineering from the Indian Institute of Technology in Madras, and master’s and doctoral degrees in systems science and mathematics from Washington University in St. Louis, Missouri.
An IEEE Fellow, he has received the Donald P. Eckman Award of the American Automatic Control Council.
Dr. Manfred Morari, Professor and Head of the Automatic Control Laboratory at the Swiss Federal Institute of Technology in Zurich, has developed several groundbreaking theoretical techniques for the design of automatic control systems. These techniques and his innovative insights have profoundly affected industrial practice and control research directions over the last 25 years. They have improved the quality control in chemical production facilities and have reduced the energy requirements and emissions in refineries.
Dr. Morari's current research focuses on hybrid systems, where the behavior can switch between different modes.The tools his group developed for controller design and analysis for hybrid systems have dramatically reduced engineering effort and on-line computation requirements. As a result, these automation systems have been implemented on a wide range of applications, including traction control for automobiles, torque control for electrical drives and energy management for cement mills. An IEEE Fellow, Dr.Morari is a member of the U.S. National Academy of Engineering.
Dr. John Doyle has applied complex ideas of robust design and control to many fields and is working on a unified theory of control in engineering, physics and biology. His innovative work strongly contributes to the human understanding of multi-variable systems, with implications well beyond his field. For nearly three decades, he has served as a consultant to Honeywell's Systems and Research Center in Minneapolis, Minnesota, and since 1986, he has been a professor of electrical engineering, bioengineering and control and dynamical systems at Caltech in Pasadena, California. An IEEE member, Dr. Doyle has received many awards including the IEEE W.R.G. Baker Prize Paper Award, two IEEE Control Systems Society George S. Axelby Outstanding Paper Awards and the IEEE Power Engineering Society Hickernell Prize Award. The holder of two patents, Dr. Doyle has published more than 30 works and co-authored two books
Dr. Pravin Varaiya, Nortel Networks Distinguished Professor in the Electrical Engineering and Computer Science Department at the University of California at Berkeley, has greatly influenced the current thinking of stochastic control systems. Applications of his work range from wireless networks to urban economics and power systems. His research in transportation led to the prototype Performance Measurement System, which will be deployed throughout California in July, 2002. A Fellow of the IEEE and a member of the National Academy of Engineering, he has written or co-authored more than 250 technical papers and has written such books as Stochastic Systems: Estimation, Identification, and Adaptive Control.
Dr Varaiya’s honors include a Guggenheim Fellowship and an IEEE Control Systems Best Paper Award. From 1979 to 1989, he co-chaired the Faculty of Human Rights in Central America.