Much research has recently been done on adapting architectural resources of general-purpose processors to save energy at the cost of increased execution time. This work examines adaptation control algorithms for such processors running real-time multimedia applications. The best previous algorithms are mostly heuristics-based and ad hoc, requiring an impractically large amount of application- and resource-specific tuning. We take a more formal approach that does not require the large tuning effort of previous approaches, and yet obtains average energy savings comparable to the best previous approach. We pose control algorithm design as a constrained optimization problem: what configuration should be used at each point in the program to minimize energy for a targeted performance given that each configuration has a different energy-performance tradeoff at each point? We solve this with the method of Lagrange multipliers, which assumes knowledge of the energy-performance tradeoffs. We develop a technique to estimate these tradeoffs using properties of multimedia applications. Our technique is likely extendible to other application domains. We compare our algorithm to the best previous algorithm for real-time multimedia applications, which is heuristics-based. We demonstrate the practical difficulty of the tuning process for the previous algorithm. Compared to a painstakingly hand-tuned version of that algorithm, our new algorithm provides similar energy savings through a more formal approach that does not need such heroic tuning, making it practical to implement.