This paper presents an innovative hierarchical feedback adaptation method that efficiently controls the dynamic QoS behavior of real-time distributed data-flow applications, such as sensor-based data streams or mission-critical command and control applications. We applied this method in the context of the Real Time Adaptive Resource Management1 system, a middleware architecture for resource management with support for integrated services, developed at the Honeywell Technology Center. We present the analytical model for feedback adaptation for periodic distributed data-flow applications and we describe experimental results for an Automatic Target Recognition pipeline application and the impact of hierarchical feedback adaptation on the application behavior and its QoS parameters.