With the coalescence of the advanced technologies such as powerful processors, fast networks, and concurrent programming, it is possible to begin to challenge traditional avionics architectures used for navigation and flight control, particularly on UAV platforms. Timing uncertainty in data delivery and computational rates is a challenge in these new architectures. This paper looks specifically at variance task computational rates. A control application is decomposed into tasks, which are managed by a scheduler. This paper demonstrates that it is possible to move task scheduling from a design-time activity to a run-time activity. This paper outlines the design of state-based schedulers to adjust the computational update periods of periodic tasks. The schedulers are shown to produce performance results comparable with static schedulers but with substantially lower processor utilization. Moreover, the processor utilization is dynamic and responds to the system based on specified system performance metrics.