Prediction and Control of Complex System Dynamics
A complex system is usually defined as a system whose dynamics is hard to describe, predict or control. The complexity may arise due to uncertainties, nonlinearities, sensitivity to initial conditions and unpredictable interactions between the elements of the system.
In this talk, Iʼm going to present the prediction and control of three different complex systems: Automotive internal combustion engine, aircraft control system including the pilot brain and air traffic control system with human and automation elements. For the internal combustion engine, Iʼll show an adaptive control design that weʼve developed at Massachusetts Institute of Technology and successfully implemented for the control of idle speed and fuel-to-air ratio control loops. For the aircraft-pilot control system, Iʼll present a control allocation method that weʼve developed to detect and compensate an abnormal aircraft-pilot coupling called “Pilot Induced Oscillations”, and successfully tested with real pilots at NASA Ames Research Center. Finally, for the air traffic control system, Iʼll present a game theoretic framework to predict the evolution of this complex
system with human elements.
Yildiray Yildiz is an associate scientist at NASA Ames Research Center, employed by U.C. Santa Cruz. He received his B Sc. degree from Middle East Technical University in 2002, M Sc. degree from Sabanci University in 2004 and PhD degree from Massachusetts Institute of Technology in 2009.
After completing his PhD, Yildiz joined NASA Ames Research Center as a postdoctoral associate, employed by U. C. Santa Cruz. In 2010, he became an associate scientist at the same institution.
Dr. Yildiz is the recipient of a best student paper award and a NASA Group Achievement Award “for outstanding technology development of the CAPIO system at the Vertical Motion Simulator supporting NASA's Green Aviation Initiative.” He was in program committees for several conferences and is a reviewer for several journals. He was a member of the AIAA Guidance, Navigation and Control Technical Committee from 2010 through 2013. His research was supported by Ford Motor Company and NASA Ames Research Center Innovation Funds. His research interests lie at the intersection of control theory and applications to aerospace and automotive systems.