Decentralized Controllers for Uncertain Linear Systems

The need for decentralized control arises in large-scale systems, where centralized control is impossible or impractical. Applications include electrical power systems, flexible structures, and flow control. These large-scale systems are often highly uncertain, which complicates the control problem. In this seminar, I will present two new decentralized control techniques for highly uncertain linear systems.

The first technique is a decentralized adaptive controller for command following and harmonic disturbance rejection. This approach requires local full-state measurement but does not require any nonlocal state measurement.

The second technique, called decentralized filtered dynamic inversion, applies to command following and disturbance rejection for minimum phase systems. This controller requires limited model information and only local output measurement. Unlike the adaptive technique, the disturbances need not be harmonic or known.

Jesse Hoagg is an Assistant Professor of Mechanical Engineering at the University of Kentucky. His research interests include decentralized control, adaptive control, robust control, and system identification with applications to flight control, flow control, and structural control. Prior to joining the University of Kentucky, Dr. Hoagg was a postdoctoral research fellow at the University of Michigan and worked for the consulting firm McKinsey & Company. Dr. Hoagg received the Ph.D. degree in aerospace engineering from the University of Michigan in 2006. Dr. Hoagg also received the M.S.E. degree in aerospace engineering from the University of Michigan, the M.S. degree in mathematics from the University of Michigan, and the B.S.E. degree in civil and environmental engineering from Duke University.