Power hardware-in-the-loop (PHIL) is a state-of-the-art simulation technique that combines real-time digital simulation and hardware experiments into a closed-loop testing environment. The transportation delay or comm...
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ISBN:
(纸本)9781728154145
Power hardware-in-the-loop (PHIL) is a state-of-the-art simulation technique that combines real-time digital simulation and hardware experiments into a closed-loop testing environment. The transportation delay or communication latency impacts the stability and accuracy of PHIL simulations. In this paper, for the purpose of synchronizing the PHIL output signal and promoting both the stability and accuracy of PHIL simulation, a hybrid compensation scheme is proposed to compensate for the time delay in the PHIL configuration. A model-based compensator is implemented to shift the time delay out of the PHIL closed-loop to enhance PHIL stability. A time delay compensation model and its equivalent inverse model are employed in the PHIL closed-loop to compensate for the time delay. A phase lead compensator and digital linear-phase frequency sampling filter (FSF) are candidate compensation models to compensate for the time delay and reshape the phase curve on a harmonic-by-harmonic basis. Simulations are made to validate the effectiveness of the compensation scheme.
Brain dysfunction in the cerebral cortex, cerebellum and/or basal ganglia causes serious movement disorders such as cerebellar ataxia, Parkinson disease and so on. Compensation of hand movement by adding an external f...
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Brain dysfunction in the cerebral cortex, cerebellum and/or basal ganglia causes serious movement disorders such as cerebellar ataxia, Parkinson disease and so on. Compensation of hand movement by adding an external force will recover the motor function and will be helpful for improving the quality of patients' daily life. This paper proposes a method for compensating human hand movement on visual target tracking by adding an assistant force. Mathematical model was obtained from the measurement data of visual target tracking for each subject, and the compensator was constructed based on the model. Effectiveness of the compensation method was investigated through the experiment.
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