Through the use of Eigenmanifold theory, unforced periodic trajectories called nonlinear normal modes can be identified and excited in nonlinear mechanical systems. Applying this to repetitive tasks in robotic systems with elastic components can drastically reduce energy consumption, as normal modes in steady-state require no additional control effort. However, existing control methods for exciting nonlinear normal modes have so far only assumed full actuation. Consequently, these techniques are incompatible with series elastic joint robots, even though they represent a significant subclass of physical systems with elastic elements. Additionally, the calculation and parameterization of Eigenmanifolds for high-dimensional systems generally remains a complex task and is difficult to scale. While existing literature aims to avoid forced evolutions or model cancellation, we instead lean into this approach. By rephrasing Eigenmanifold-based control as a trajectory tracking problem, standard techniques for elastic joint robot trajectory tracking control can be employed. Furthermore, obtaining theoretical guarantees on global stability becomes possible. In this work, a new modular control architecture is presented that integrates trajectory tracking feedback control with Eigenmanifold theory to dynamically generate and track hyper energy-efficient oscillatory movements in underactuated systems. This approach enables the excitation of nonlinear normal modes using standard trajectory tracking controllers, while preserving energy-efficient properties desired from Eigenmanifold-based controllers. We first discuss the theoretical validity and energy-efficiency of this control architecture, and then test the architecture in simulation for a variety of use-cases and controllers.