• Advances in adaptive control theory: gradient- and derivative-free approaches 

      Yucelen, Tansel (Georgia Institute of Technology, 2011-09-29)
      In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures. We first present a novel Kalman filter based approach for approximately ...
    • Neural Network Augmented Kalman Filtering in the Presence of Unknown System Inputs 

      Sattigeri, Ramachandra J.; Calise, Anthony J. (Georgia Institute of TechnologyAmerican Institute of Aeronautics and Astronautics, Inc., 2006-08)
      We present an approach for augmenting a linear, time-varying Kalman filter with an adaptive neural network (NN) for the state estimation of systems with linear process models acted upon by unknown inputs. The application ...
    • Nonlinear Estimation for Vision-Based Air-to-Air Tracking 

      Oh, Seung-Min (Georgia Institute of Technology, 2007-11-14)
      Unmanned aerial vehicles (UAV's) have been the focus of significant research interest in both military and commercial areas since they have a variety of practical applications including reconnaissance, surveillance, target ...
    • Peak-seeking control of propulsion systems 

      Cazenave, Timothee (Georgia Institute of Technology, 2012-07-10)
      Propulsion systems like Turboprop engines are generally designed to operate at a narrow range of optimum steady state performance conditions. However, these conditions are likely to vary in an unpredictable manner according ...
    • Vision-based navigation and mapping for flight in GPS-denied environments 

      Wu, Allen David (Georgia Institute of Technology, 2010-11-15)
      Traditionally, the task of determining aircraft position and attitude for automatic control has been handled by the combination of an inertial measurement unit (IMU) with a Global Positioning System (GPS) receiver. In ...
    • Vision-based Target Tracking with Adaptive Target State Estimator 

      Sattigeri, Ramachandra J.; Johnson, Eric N.; Calise, Anthony J.; Ha, Jin-Cheol (Georgia Institute of TechnologyAmerican Institute of Aeronautics and Astronautics, Inc., 2007-08)
      This paper presents an approach to vision-based target tracking with a neural network (NN) augmented Kalman filter as the adaptive target state estimator. The vision sensor onboard the follower (tracker) aircraft is a ...