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 Management system, 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.