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Many modern networked real-time systems encompass complex feedback structures and require stringent timing guarantees, especially bounds on the network delay. Network Calculus (NC) is a versatile methodology to compute such performance guarantees per individual flow; in particular, some fundamental results on how to deal with feedback exist. Yet, these are restricted to simple feedback structures and are mostly constrained to an analysis at the aggregate level (not per flow). In our work, we analyze more complex feedback structures than previously investigated by reducing them to canonical structures. We transform these closed-loop systems (with feedback) into open-loop systems (without feedback) and, subsequently, perform a per-flow analysis exploiting very recent NC results on per-flow performance guarantees. In a numerical experiment, we compare our new method to the current state-of-the-art which only allows for an aggregate FIFO analysis. We also compute how feedback constraints need to be allocated to ensure that a feedback system provides the same service as the system without feedback, in a sense providing for an optimal control. Furthermore, we compare different allocation strategies under a fixed budget for the feedback constraints.