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Software mechanisms that enforce QoS guarantees often require knowledge of platform capacity and resource demand. This requirement calls for performance measurements and profiling upon platform upgrades, failures, or new installations. The cost of performing such measurements is a significant hurdle to the wide-spread deployment of open QoS-aware software components. In this paper, we introduce a new QoS-control paradigm based on adaptive control theory. The hallmark of this paradigm is that it eliminates profiling and configuration costs of QoS-aware software, by completely automating the process in a way that does not require user intervention. As a case study, we describe, implement and evaluate the control architecture in a proxy cache to provide proportional differentiation on content hit rate. Adaptive control theory is leveraged to manage cache resources in a way that adjusts the quality spacing between classes, independently of the class loads, which cannot be achieved by other cache resource management schemes, such as biased replacement policies, LRV or greedy-dual-size.