Robust Analysis and Synthesis for Linear Parameter Varying Systems

More efficient aircraft can be designed by reducing weight and structure in the wings and fuselage. This makes the aircraft more flexible leading to dynamics that change rapidly with flight condition. Linear parameter varying (LPV) systems are a useful framework to model these rapidly changing dynamics. This talk will focus on two theoretical challenges. First, it is possible to model the dynamics of flexible aircraft with high fidelity fluid/structure models. A method will be described to construct reduced-order, control-oriented models. Second, the uncertainty in the aeroelastic models must be considered in the control design. The talk will also describe analysis and synthesis tools that address this model uncertainty.

Dr. Seiler received his Ph.D. from the University of California, Berkeley in 2001. His graduate research focused on coordinated control of unmanned aerial vehicles and control over wireless networks. From 2004-2008, Dr. Seiler worked at the Honeywell Research Labs on various aerospace and automotive applications including the redundancy management system for the Boeing 787, sensor fusion algorithms for automotive active safety systems and re-entry flight control laws for NASA's Orion vehicle. Since joining the University of Minnesota in 2008, Dr. Seiler has been working on fault-detection methods for safety-critical systems as well as advanced control of wind turbines and flexible aircraft.