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The paper suggests a new iterative feedback tuning (IFT)-based approach to the design of optimal state feedback control systems. Several signal processing aspects are analyzed to reduce the number of experiments in two control system structures. The presentation is focused on second-order positioning systems applied to manufacturing and robotics leading to an original IFT algorithm. Real-time results for an experimental setup based on a DC servo system with backlash validate the new theoretical approaches.