Neural network augmented model inversion control is used to provide a civilian tiltrotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response type is Attitude Command Attitude Hold in the longitudinal channel. Similar strategies can be applied to provide for Rate Command Attitude Hold in the roll channel, and Heading Hold and Turn Coordination for the yaw motion. Conventional methods require extensive gain scheduling with tiltrotor nacelle angle and speed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time, facilitate the implementation of handling qualities, and compensate for partial failures. One of the key aspects of the controller architecture is the accommodation of modeling error. It includes an online, i.e. learningwhile-controlling, neural network with guaranteed stability. The performance of the controller is demonstrated using the nonlinear Generic Tiltrotor Simulation code developed for the Vertical Motion Simulator at the NASA Ames Research Center.