Real-time control has become increasingly important as technologies are moved from the lab into real world situations. The complexity associated with these systems increases as control and autonomy are distributed, due to such issues as precedence constraints, shared resources, and the lack of a complete and consistent world view. In this paper we describe a soft real-time architecture designed to address these requirements, motivated by challenges encountered in a distributed sensor allocation environment. The system features the ability to generate schedules respecting temporal, structural and resource constraints, to merge new goals with existing ones, and to detect and handle unexpected results from activities. We will cover a suite of technologies being employed, including quantitative task representation, alternative plan selection, partial-order scheduling, schedule consolidation and conflict resolution in an uncertain environment. Technologies which facilitate on-line real-time control, including schedule caching and variable time granularities are also discussed.