A modification of a previous predictive adaptive-optic controller is presented in this paper. Conventional adaptive-optic controllers suffer from bandwidth limitations caused by latency in their control loops. This latency severely limits their capabilities in aero-optic applications that cannot be overcome with conventional feedback techniques. Our method uses prior knowledge of flow behavior to predict future behavior, and thus overcome deadtime. We have modified our previous neural network controller to use a linearized predictor, which we demonstrate to be more accurate, more robust to noise and flow disturbances, and less computationally expensive. Our previous neural network method showed disturbance rejection in the range of 35-55% in simulation over our test conditions in the most optically-active regions, while the improved method shows disturbance rejection between 45-75% over the same range. Additionally, we demonstrate that the predictive control method is stable, even in the presence of latency uncertainty.