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Experimental study of PID auto-tuning for unsymmetrical processes
Kazuhiro Mimura,Tetsuo Shiotsuki 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
The advent of relay auto-tuning of PID controllers got rid of previous troublesome tuning procedure. However, PID control performance didn"t change so much since the tuning rule was the same as the Ziegler and Nicholsthat only use ultimate gain and ultimate period. In this paper, we propose new tuning rule especially for an unsymmetrical process. The experimental test result showed proposed rule achieved less overshoot and quicker disturbance recovery than conventional tuning rule.
Self-Tuning Control for Ratational Speed of Slider-Crank Mechanism
Hitoshi SAITO,Jun ISHIKAWA,Tetsuo SHIOTSUKI,Katsuhisa FURUTA 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper proposes a self_tuning control method based on generalized minimum variance control for rotational speed control of a slider_crank mechanism. Dynamic characteristics of the slider_crank mechanism significantly changes depending on the wheel rotational angle. Thus, to achieve a good control performance, it is necessary for the plant parameters to be identified at the each section divided into six by the wheel angle. This kind of control based on the local modeling is useful not only for such a slikder_crank mechanism but also for highly_accurate positioning control systems with significant nonlinearity. The validity of the proposed method is verified through simulations and experiments.
Emotional Level of Sadness for Normal and Dementia Subjects by NIRS
Shinichi Yoshino,Katsuhisa Furuta,Tetsuo Shiotsuki,Yukihito Suzuki,Hideto Shimizu,Hiroki Takase 동국대학교 정보융합기술원 2010 International Journal of Assistive Robotics and Sy Vol.11 No.1
This paper proposes a method to measure the level of sadness by the 52 channels signals of near infrared spectroscopy (NIRS). Normal and dementia subjects are measured while they watch the sad video story. The analysis has been done by using the first principal component of 52 measured signals, and the paper proposes to classify sadness into two classes; sequence of emotional reactions defining ‘dynamic sadness’ and accumulation of sadness defining ‘static sadness’. Both represent the feeling of sadness. They are measured quantitatively by the power over the certain frequencies and the time average of principal components of the measured NIRS signals. The measured signals of the normal subjects show that weight distribution parameters are rather large in the prefrontal cortex area corresponding from 32 to 52 channels, which indicates the subjects understanding the story. This paper shows that the difference of the sad emotion between the normal and dementia subjects is found by using both time average and power of the first principal component of NIRS signals over the whole measurement time. These informations may be used to test brain activities of both normal and dementia subjects. The proposed approach can be used to measure other brain activities using NIRS signals.