In this study, we propose a new parameter tuning method for robotic manipulators which enables to tune linear feedback gain and dynamical parameters in exact linearization controller from only one-shot experimental data. This method is an extension of FRIT (Fictitious Reference Iterative Tuning) to nonlinear systems. Tuning process of FRIT method can be considered as model matching to the unknown plant. In this study, by providing mathematical model of the unknown plant, we can find parameters which achieve the desired response for any reference. In order to show validity of this method, we apply this method to resolved acceleration controller for a SCARA type robot, and simulation was performed. Furthermore, we analyzed the effect of error in provided model of controller and the dependence of tuned parameters on experimental data.

In order to grasp the biological information on a daily basis, more detailed information can be obtained as the number of measurements increases. In blood glucose level measurement, it is necessary to reduce the burden on the subject in order to increase the number of measurements, and non-invasive measurement is required. We measured the strain of the radial artery using the Fiber Bragg Grating (FBG) sensor, which is an optical fiber type strain sensor. The FBG sensor was a non-invasive measurement method that could measure strain signals simply by installing it on the surface of the living body on the radial artery. This strain signal was continuously measured by the developed wearable FBG sensor system. This study was conducted on a total of 9 subjects, 7 males and 2 females. A calibration model for calculating blood glucose level was constructed by Partial Least Squares (PLS) regression analysis using the signal waveforms measured by 7 subjects. The data of the remaining two subjects were substituted into the calibration model to calculate the predicted blood glucose level. The blood glucose level prediction accuracy was 19mg/dl, and all Error Grid Analysis (EGA) results were plotted in the A or B zone. The data of these two subjects were measured continuously, it was possible to show the transition of blood glucose level. Therefore, it was shown that the transition of the blood glucose level of the subject whose blood glucose level calculation calibration model has no data can be calculated from the signals continuously measured by the portable FBG sensor system.

Judder is well known as a vibration that occurs in a dry clutch. In order to maintain the ride quality and quietness of dry clutches, research on judder analysis and mechanical design to suppress judder is actively pursued. This paper describes the design and implementation of robust control techniques as an approach to suppressing judder during gear shifting in traction-controlled transmissions. This paper is concerned with transmissions that exhibit strongly nonlinear frictional characteristics that can only be approximated by higher order polynomials. Specifically, the coefficient of friction varies significantly nonlinearly with the rotational speed during gear shifting. In this paper, the controller is designed by expressing this nonlinear property as the uncertainty of the frequency. Simulation and bench test results are presented to validate the validity of such an approach. The results show that judder-free shifting is possible with the proposed approach. Furthermore, the requirements of three controllers are presented by analyzing the robust controllers.

To operate trail running safely while reducing costs, we considered a system that quickly detects participants who are off course or need urgent rescue. The system adopts long short-term memory for the prediction of the trail running participant time.

In the previous paper, we proposed a method to stabilize the air over a heater by ultrasonic standing wave for better vision sensing. The phenomenon was not fully understood. This paper reports the observation results by particle image velocimetry.