David Quinn Mayne, an engineer whose work has been instrumental in optimizing control techniques for industrial applications, is being honored by the IEEE with the 2009 Control Systems Award. IEEE is the world's leading professional association for the advancement of technology.
The award, sponsored by the IEEE Control Systems Society, recognizes Mayne for contributions to the application of optimization to modern control theory. The award was presented on Dec. 17, 2009, at the Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC) in Shanghai, China.
Among Mayne's many contributions to the development of control theory, probably the most important is his work on model predictive control (MPC). With the ability to deal with nonlinearities and hard constraints in an intuitive manner, MPC joins open- and closed-loop techniques to avoid the complicated task of determining feedback control laws offline, and instead repeatedly solves an optimal control problem online to determine the control action to be applied to the plant or process. Model predictive control is used in thousands of applications, such as in chemical plants and oil refineries, and is a major component of advanced control technology sold by process control vendors.
Mayne's pioneering work in the area of MPC provides a rigorous mathematical basis for analyzing MPC algorithms. His general methodology and toolset for studying the stability of MPC loops has become highly influential, and he has built on these ideas by describing new strategies for handling nonlinear systems and achieving robust MPC. The impact of his work will continue to be seen as MPC finds increased use in today's high-speed electromechanical, aerospace and automotive systems.
Mayne was also the first to describe what is now known as "particle filtering,"which has become a central part of nonlinear filtering. It is now used for vehicle autopilots, aircraft tracking, and predictingcommodity prices. He also introduced the concept of differential dynamic programming as a method for solving optimal control problems, was the first to show that Kalman filtering can be used for non-stationary parameter estimation, and provided early guidelines for adaptive control, which is important in the aerospace industry. Overall, his published work has been cited more than 2,600 times according to the ISI Web of Knowledge service.
An IEEE Life Fellow and Fellow of the Institution of Engineering and Technology, the Royal Society of London, and the Royal Academy of Engineering, Mayne received the Sir Harold Hartley Medal in 1986 from the Institute of Measurement and Control for contributions to technology of measurement and control of outstanding merit. He is currently an emeritus professor and senior research investigator at Imperial College London.