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The American Institute of Aeronautics and Astronautics (AIAA)

is the world's largest technical society dedicated to the global aerospace profession.

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    • AIAA Foundation
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    Course Outline

    Course Outline

    1. Motivation and Goals

    2. Nonlinear Analysis and Lyapunov Stability Theory

    3. Adaptive Control
      1. Basic Concepts
      2. Model Reference Adaptive Control: A Problem Formulation
      3. Approximate Model Inversion Based Adaptive Control
      4. Neural Networks and Neuroadaptive Control
      5. Modifications to Adaptive Control
        1. Classical Modifications to Ensure Bounded Weight Estimates
        2. New Modifications to Improve Transient Response and Robustness

    4. Kalman Filtering in Adaptive Control
      1. Kalman Filter Modifications
      2. Kalman Filter Based Adaptive Control

    5. Concurrent Learning Adaptive Control
      1. Concurrent Learning Adaptive Control of Nonlinear Systems
      2. Online Selection of Data for Concurrent Learning: A Singular Value Maximizing approach
      3. Concurrent Learning Adaptive Control of Linear Systems
      4. Leveraging exponential stability to guarantee performance and stability bounds

    6. Derivative-Free Adaptive Control 
      1. A New Uncertainty Parameterization for Fast Adaptation
      2. Disturbance Rejection in the Context of Adaptive Control
      3. Guaranteed Transient and Steady-State Performance

    7. Output Feedback Adaptive Control 
      1. A Parameter-Dependent Riccati Equation Approach
      2. Derivative-Free Output Feedback Adaptive Control

    8. Decentralized Adaptive Control of Large-Scale Interconnected Systems

    9. A Kernel Hilbert Space Approach to Online Selection of Bases in Neuroadaptive control

    10. Adaptation in the Presence of Actuator Dynamics and Saturation: Pseudo Control Hedging

    11. Adaptive Guidance and Control for Fault-Tolerant Flight Vehicles

    12. Implementation of Adaptive Controllers on Aerial Vehicles
      1. Implementing adaptive controllers for flight vehicles
      2. Concurrent Learning Adaptive Control: Discussion of Flight Test Results
      3. Derivative-Free Adaptive Control: Discussion of Flight Test Results
      4. Adaptive Loop Recovery: Discussion of Flight Test Results
      5. Fault Tolerant flight control: Discussion of Flight Test Results

    13. Future Research Directions
      1. Making a link between machine learning and adaptive control
      2. Uncertainty in Control Effectiveness and Actuator Failures
      3. Unmodeled Dynamics and Unmatched Uncertainties
      4. Adaptation in the Presence of Actuator Dynamics