My graduate research focuses on adaptive control of aircraft. My current goal is to improve the performance of a previously developed neural controller by adding constraints to the algorithm that trains the neural networks (the "intelligent" part of the controller). Control systems that have the ability to learn about and adapt to their system can produce better performance over wider operating ranges than traditional controllers. These controllers could be used in a wide variety of systems including, but not limited to, aircraft, naval vessels, spacecraft, and interplanetary robots.