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This paper presents the development of a robust adaptive controller for the dynamics of a quadrotor unmanned aerial vehicle (UAV) in the presence of linear-in-the-parameter uncertainties and bounded exogenous disturbances. The controller is designed to asymptotically track a desired position and yaw angle trajectory via a modular adaptive update law and a robust integral sign of the error (RISE) feedback term. A Lyapunov-based stability analysis is used to prove asymptotic tracking of the desired states and to ensure all closed-loop signals remain bounded.

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This paper is an exposition on the design of robust observer-based adaptive autopilots for aerospace systems. Using a rocket boosted missile as an example, we will discuss systematic design principles to meet closed-loop autopilot robustness and performance criteria. The controller consists of decoupled lateral and longitudinal linear gain scheduled optimal baseline designs with servomechanism acceleration tracking and observer-based adaptive augmentation. We will demonstrate improved robustness with observer-based adaption to various uncertainties including significant discrepancies in aerodynamic coefficients, center of gravity shifts, and actuator failures. These results support the practicality of observerbased adaptive output feedback laws for the control design of uncertain aerodynamic systems.

This paper presents the development of a saturated robust integral of the sign of the error (RISE) feedback controller for an airfoil section undergoing store-induced limit cycle oscillations. The controller is designed to asymptotically track the airfoil section angle of attack (AoA) in the presence of structural and aerodynamic uncertainties without breaching actuator limits through a smooth saturation function. A Lyapunov-based stability analysis is used to prove global asymptotic tracking of the AoA. Simulation results demonstrate the performance of the developed controller.

Limit cycle oscillations (LCOs) affect current fighter aircraft and are expected to be present on next generation fighter aircraft. Current efforts in control systems designed to suppress LCO behavior have either used a linear model, restricting the flight regime, require exact knowledge of the system dynamics, or require uncertainties in the system dynamics to be linear-in-theparameters and only present in the torsional stiffness. Furthermore, the aerodynamic model used in prior research efforts neglects nonlinear effects. This paper presents the development of a controller consisting of a continuous robust integral of the sign of the error (RISE) feedback term with a neural network (NN) feedforward term to achieve asymptotic tracking of uncertainties that do not satisfy the linear-in-the-parameters assumption. Simulation results are presented to validate the performance of the developed controller.

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