A conventional rowing machine was modified with an electric motor and a robust impedance control system to mimic the behavior of a conventional rower and subsequently expand its versatility. The powered machine has programmable impedance and can produce controlled forces during the return stroke, allowing for eccentric exercise. Conventional rowers do not allow eccentric loading, an exercise modality known to contribute significantly to the efficacy of training. Eccentric loading is particularly important to diminish the detrimental effects of humans operating in microgravity for long periods of time. Conventional rowers include a flywheel, a fan and a freewheeling clutch. These elements were removed and replaced by a torque-controlled motor and a belt transmission selected on the basis of the forces and velocities encountered in the rowing exercise. A hybrid dynamic model was developed for the conventional rowing machine to account for its force-velocity characteristics and the transitions between the coupled (pull stroke) and the decoupled (return stroke) of the freewheeling clutch. Machine parameters such as flywheel inertia, air damping coefficients and return spring constants were identified from a set of experimental data and fitted to the model. The model was then used to design the robust hybrid impedance controller which includes a virtual flywheel and a force sensor to determine the transitions between pull and return strokes. The controller reproduces the operation of the original machine and can also be programmed to produce arbitrary impedances. The paper describes the hybrid dynamic model and control approach and the real-time experimental trials.
- Dynamic Systems and Control Division
Design and Hybrid Impedance Control of a Powered Rowing Machine
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de las Casas, H, Richter, H, & van den Bogert, A. "Design and Hybrid Impedance Control of a Powered Rowing Machine." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T38A002. ASME. https://doi.org/10.1115/DSCC2017-5243
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