Special Issue on “Smart Systems and Instrument Control Technology—Contribution to SDGs—”
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Shohei Yamamoto, Takuya Kinoshita, Shin Wakitani, Toru Yamamoto, Yasun ...
2023Volume 143Issue 3 Pages
216-221
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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In painting processes, to prevent the occurrence of painting defects, the rotational speed of the bell cup should be adjusted online based on the painting quality. However, there is a considerable time-delay between the painting process and the evaluation of painting quality. This paper proposes a database-driven painting quality predictor, which has a mechanism to adaptively change the threshold to classify through learning to reduce the delay. A numerical simulation is performed to verify the effectiveness of the proposed method. As a result, the accuracy of the proposed method is superior to that of the conventional method.
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Ken Fujisawa, Masanori Takahashi
2023Volume 143Issue 3 Pages
222-228
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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Every ecosystem is composed of multiple species. Hence, extinction of a specie might affects lives of other species, and of course, human life is influenced by populations of various species. Unfortunetaely, in general, it is quite difficult to recognize signs of extinction. In this paper, for a competition system of three species, a new alarm system is developed to notify extinction trends. The method exploits an adaptive tracker to estimate the parameters of the mathematical model of the competition system, and alerts when the estimated parameters would induce extinction. Furthermore, theoretical and numerical analysis are explored to confirm the effectiveness of the proposed alarm system.
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Masato Tanaka
2023Volume 143Issue 3 Pages
229-235
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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In this paper, general-purpose feedforward control design for heating process systems is described. The feedforward control function should be implemented to a local PID temperature controller. The controller is supplied to the heating process equipment manufacturer. In composition of the business, the adequacy of the relations between companies of the control technology is an important issue.
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Hiroyuki Sogo, Tomohiro Henmi, Kousei Yoshizawa, Gou Saziki, Atsuro Yo ...
2023Volume 143Issue 3 Pages
236-241
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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The purpose of this study is to devise and evaluate a coaching method by using kinematic feature values before and after coaching for beginners as a new quantitative coaching method in batting motion. After the coaching using the proposed new method for two beginners as subjects, the feature values of batting motion of both beginners when doing the tee batting are significantly closer to those of the experts. It proves the proposed new quantitative coaching method have a certain effect on a progress of beginners batting. In the future work, in order to evaluate the statistical effectiveness of proposed coaching method, the numbers of beginners as subjects will be increased.
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Natsuki Kawaguchi, Kenta Watanabe, Nozomu Araki, Takao Sato, Masaharu ...
2023Volume 143Issue 3 Pages
242-249
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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This paper proposed a thrust vector norm minimization control method for a twin-rotor drone model. The model represents a simple input-redundant drone that can operate two rotors for 1-DoF (DoF: Degree of Freedom) of motion. The proposed method adaptively minimizes the norm of the generated thrust vector even if the characteristics of each rotor are unknown. This is expected to achieve efficient control in terms of minimizing the energy consumption for thrust generation in the drone. The effectiveness of the proposed control system is demonstrated through numerical examples.
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Yoshihiro Matsui, Hideki Ayano, Shiro Masuda, Kazushi Nakano
2023Volume 143Issue 3 Pages
250-257
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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This paper gives a method for converting finite-length transient response signals with non-zero steady-state values into the frequency domain. In the method, the signal is discrete Fourier transformed after adding a linear function without DC component. The linear function is equivalent to the AC components of a step function whose amplitude is the steady-state value of the signal in the frequency domain. The usefulness of the proposed method is confirmed by a numerical experiment and an experiment to estimate the frequency characteristics of the transient response signals obtained from an actual position control system for a mass-spring-damper system.
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Yasuhiro Makino, Shota Oguma, Shuichi Ohno, Kazuhiro Iwasaki
2023Volume 143Issue 3 Pages
258-265
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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In the construction industry, it is desirable to develop a system to easily judge skills of workers in order to effectively pass on the skills of skilled workers to unskilled workers. This report proposes a skill analysis method in hydraulic excavator operators using a convolutional autoencoder (CAE) that is capable of nonlinear mapping to low dimensionally space. CAE is trained with the operation data of a skilled operator to acquire characteristics of the skilled operator. Then, the operation data of an unskilled operator is input to the trained CAE to analyze the unskilled operator's skill. CAE detects operations of the unskilled operator containing features that differ from the operation of the skilled operator out of many operations. First, it is confirmed that CAE can save information of the operation data in a low dimensional space than principal component analysis that is a linear mapping for dimensionality reduction. Next, the result of the proposed method for the unskilled operator is shown. Effectiveness of the result is validated by comparing a few operation data of both operators detected by the proposed method.
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Motoya Suzuki, Osamu Kaneko
2023Volume 143Issue 3 Pages
266-275
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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In this paper, we propose data-driven control for the case of that the structure of the ideal controller is unknown. In this case, it is natural to implement FIR typed controller. Here, we utilize FRIT for the case of FIR typed inverse controller. In general, FIR might have unnecessarily large number of its taps. To prevent it, we also utlize LASSO regression so as to realize FIR typed inverse controller in as less numbers of the tap as possible. Moreover, we also utilize data-driven prediction to determine hyper parameters required in LASSO regression. The validity of our proposed method is verified by using experiments.
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Daisuke Toyota, Koutarou Nakano, Kiyoshi Ochi, Takuya Kinoshita, Shin ...
2023Volume 143Issue 3 Pages
276-280
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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The database-driven (DD) PID control is a method of using a database to adjust PID parameters. System input/output data are stored in the database. The DD-PID control can be expected to expand the technology to smart systems such as state determination. In this paper, a state value determination method using the operation results of the DD-PID control is newly proposed. The proposed method has the same data structure as the DD-PID control and can determine the current system state value based on a DD approach. In addition, the proposed method improves accuracy by using logit transformations near the upper and lower limits of the system state value range. The effectiveness of the proposed method is verified by a numerical simulation.
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Zhifeng Li, Zhe Guan, Toru Yamamoto, Sigeru Omatu
2023Volume 143Issue 3 Pages
281-288
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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As a nonlinear control approach, a database-driven PID (DD-PID) controller has been proposed that uses distance calculations of an initial database to tune PID parameters. However, sorting operations are required in extracting neighborhood data from the database, which imposes a large computational load. Therefore, it is impossible to finish this computation within a restricted sampling period in control systems with fast response time and insufficient memory capacity. On the other hand, the cerebellar model articulation controller (CMAC) has advantages for these problems and has similar constructs to the DD approach. Therefore, this paper combines advantages of these two approaches, and proposes a CMAC-PID controller design based on off-line optimization of a database. Finally, a comparison with conventional off-line CMAC-PID controller and DD-PID controller through simulations are considered.
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Yuta Susawa, Keita Murai, Kazuo Kawada
2023Volume 143Issue 3 Pages
289-296
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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In order to make the realization of Society 5.0, which contributes to the achievement of the SDGs, a focus has been placed on human resource development to create new value in the Sixth Science, Technology and Innovation Plan. In addition, a development method called “Model Based Development”, in which simulations are conducted using mathematical models, is being promoted in industry. In this study, we develop and practice Model Based Development Thinking education at the junior high school level, and verify its educational effectiveness. Specifically, it is the development of learning materials for proportional control focusing on the characteristic of a sensor, using Advanced Emergency Braking System as the subject. In addition, this research is aimed at the SDGs goals : (4) Quality Education, (7) Affordable and Clean Energy, and (9) Industry, Innovation and Infrastructure.
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Kouta Kosaka, Shiro Masuda, Mitsuru Toyoda, Yoshihiro Matsui
2023Volume 143Issue 3 Pages
297-304
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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This paper considers the VRFT (Virtual Reference Feedback Tuning), which is a data-driven controller parameter tuning method using one-shot input-output data, and aims to improve control performance in the case of using noisy data. The paper focuses on pre-filter designs for performance improvement on model matching properties, and proposes a kernel regularization method to mitigate the influence of the noise in the collected data. Furthermore, this paper shows how to determine the hyperparameters in the kernel as well. Finally, the effectiveness of the proposed method is demonstrated using numerical simulations.
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Yukinori Nakamura, Tsuyoshi Yamashita, Shin Wakitani, Kentaro Hirata
2023Volume 143Issue 3 Pages
305-311
Published: March 01, 2023
Released on J-STAGE: March 01, 2023
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This paper considers data-driven type generalized minimum variance control (GMVC) for p-inputs/q-outputs (p > q) multivariable systems with static nonlinearity. In the proposed approach, an autoencoder, which can extract the feature of input data, is used. First, an encoder converts input data with p dimensions into that with q dimensions. Then, a GMV controller is designed by using the dimension-reduced input data. Finally, the nonlinearity of a plant is compensated by a decoder, which reconstructs the input data with p dimensions. The effectiveness of the presented approach is evaluated using a numerical example.
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