This paper presents the application of a model‐based iterative learning control technique to position tracking of a piezoelectric system. Identification of the closed‐loop piezoelectric system was undertaken first, and then an iterative learning control methodology based on the identified model was implemented for dynamic tracking control of the actuator. The methodology differs from the conventional iterative learning scheme in that it takes into account the difference of the one‐step‐ahead predictive input between two successive iterations. The methodology compensates for the predictive input difference as well as the causal error in the previous iteration. The results of the experiments prove the excellence of this technique for precision tracking control of the piezoelectric actuator.
Patents contain much significant technical information which can serve as an indicator of technological and economical development. This study attempts to forecast the development of the biped robot walking technique in Japan by use of the patent data obtained from the Japan Patent Office. The study applies linear regression to the patent data using three S-curve models developed by Loglet Lab, Pearl, and Gompertz individually. Various parameters inherent to each model including the least sum of modulus error and the least mean of square error of the model are analyzed. The most appropriate model for measuring the inflection point, the growth and the saturation time of the technique is described. Based on the Gompertz model analysis, this study finds that the biped robot walking technique will continue to develop for several decades in Japan and the saturation period is estimated to be around the year 2079-2082. This finding can help related researchers and managers in the robot field to foresee the development trend of the biped robot walking technique in this century.
Abstract-This study presented to insert a small-scaled microphone of the ear-set of a smart mobile (Amazing A6, Taiwan MobileTM) into an eartip of the stethoscope, the sound can be transmitted by the mobile when it dialed to another phone or mobile. In this study, we employed another smart phone (Galaxy R GT19103, SamsungTM) to be the receiver. The results were showed by spectrogram which demonstrated the components of frequencies of the sounds. Finally, we proposed to improve the study by database.
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