Jeffrey B. Burl
- EERC 710
Associate Professor, Electrical and Computer Engineering
- PhD, Electrical Engineering, University of California - Irvine
- MS, Electrical Engineering, University of California - Irvine
- BS, Physics & Astronomy, University of Michigan
Jeffrey B. Burl is an associate professor of electrical and computer engineering at Michigan Technological University. He received a BS in Physics and Astronomy, with honors in astronomy and distinction, in 1978 from the University of Michigan in Ann Arbor, as well as two degrees from the University of California-Irvine: an MS in Electrical Engineering, in 1982, and a PhD in Engineering, in 1987. His current research interests include image-based control systems for robots and aerospace vehicles, automotive control, adaptive control, robust multivariable control theory, and applications of control and signal processing. Burl has worked on the international space station, missile autopilot design, attitude slewing for the crew and equipment retriever for the space station, adaptive fuel control for automotive engines, autonomous robot control, and numerous other control and signal processing applications. He has published a book titled "Linear Optimal Methods" and has published papers in the IEEE Transactions on Signal Processing, the IEEE Transactions on Image Processing, the AIAA Journal of Guidance, Control, and Dynamics, the ASME Journal of Dynamic Systems, Measurement, and Control, and the SAE Technical paper series, among others.
Areas of Interest
- Control systems
- Development of a low cost collision avoidance system for general aviation (FAA)
- Intelligent control of automotive manufacturing systems (GM)
- Adaptive optics (AFOSR)
- Reentry body control (SSP)
- Image motion analysis and image based tracking systems (AFOSR)
- Control theory: extended H estimation; uncertainty reduction in µ-synthesis (SSP)
- Astronomy/observatory upgrades (fun)
- Arbuckle, J. S., Burl, J. B. "Indicated Mean Effective Pressure Estimator Order Determination and Reduction When Using Estimated Engine Statistics", ASME Journal of Dynamic Systems, Measurement, and Control (Vol. 131, No. 1, pp. 011007-1 to 011007-10). (Published)
- Linear Optimal Control: H2 and H Methods, Addison-Wesley Publishing, 1999. Book presents linear quadratic Gaussian design, H controller design, and µ-synthesis controller design along with modern tools for performance and robustness analysis.
- Mercury Marine Corp., "Engine Running Quality Optimization via Adaptive Engine Calibration," 2003.
- Kimberley-Clark Corp., "Controls Lab Upgrade,", T. Schulz, J. Burl, and D. Stone.
- U. S. Department of Energy, "Interdisciplinary Center of Advance Propulsion (ICAP)," 1998-2000, Principle Investigator: D. Abata, Co-Investigators: C. Anderson, J. Burl, L. Evers, C. Fredrick, J. Johnson, D. Michalek, W. Milligan, F. Morrison, M. Mullins, K. Rundman, J. Sutherland, and J. Yang.
- GM Foundation, "Neural Networks and Fuzzy Logic in Automobile and Automobile Manufacturing Control Systems," 1996-2000, Principle Investigator: J. Burl Co-Investigator: Fahmida Chowdhury.
- FAA Grants for Aviation Research, "Development of a Passive Cockpit Display of Traffic Information/Collision Alert System," 1996-1998.
- AFOSR Summer Research Extension Program (Phillips Laboratory), "Improved Methods of Tilt Measurement for Extended Images in the Presence of Atmospheric Disturbances Using Optical Flow," 1995, Co-Investigator: John Lipp.
- Strategic Systems Programs, "Theater Ballistic Missile Defense Interceptor Optimization," 1992/1993.