Date of Award

Spring 2024

Embargo Period

4-14-2025

Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aerospace Engineering

Department

Aerospace Engineering

Committee Chair

Richard Prazenica

First Committee Member

Kadriye Merve Dogan

Second Committee Member

Eric Coyle

Third Committee Member

Troy Henderson

College Dean

James Gregory

Abstract

Aerospace systems often exhibit nonlinear, time varying dynamics. Expansive mission profiles, fuel burn or transfer and payload deployments or slung loads can supply additional complexity that can excite the plant dynamics and result in undesirable performance. Because of these often unknown dynamical effects in aerospace systems, an emphasis is placed on controller robustness as significant safety risks are present. Due to the difficulty of predicting uncertainties, robust control can be achieved in two distinct ways. The first approach is to design a control law to be tolerant to a large amount of uncertainty, and the second is to design a control law that can adapt to changing system parameters. It is well known that adaptive controllers can respond to external disturbances and uncertain or nonlinear dynamics. This dissertation investigates the development of adaptive control laws to stabilize and control a class of nonlinear, time varying systems. A direct model reference adaptive control architecture, which includes actuator hedging in the reference model to address actuator bandwidth limitations and uncertainty, is designed and implemented to compensate for dynamical effects that could, for example, be caused by a slung load suspended from a quadrotor. A variety of systems that belong to the same class are presented including a rotating tank system with fluid slosh, and quadrotors with slung loads or actuator failures. A direct model reference adaptive controller complete with a PID or LQR controlled reference model is implemented in each case to enable the system to track attitude trajectories generated by a reference model. Modifications to a baseline direct model reference adaptive controller are applied to attenuate the effects of measurement noise and actuator dynamics. The stability of this control law is investigated via Lyapunov analysis. Simulation results are provided showcasing overall controller performance of attitude control in the presence of both internal and external disturbances, measurement noise, actuator dynamics and actuator failure.

Available for download on Monday, April 14, 2025

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