現代のグローバル化された社会では，一国の経済状況が他国に伝搬することはもちろんのこと，気候変動や感染症といった地球規模の課題もグローバルに連鎖し，経済成長や貧困・格差等の社会問題にも影響を及ぼす時代になってきています。このような世界に対応するために2015年9月

IoT creates Big Data and tends to create heavy load in communication and in data analysis when being stored directly to the cloud computing system. Therefore, the edge computing becomes important and effective for the IoT system. On the other hand, various issues occur from the viewpoint of business. In this paper, intellectual property of PID control solution is described.

In this paper presents the activities of the research committee to date. The study of motorcycle riding skills is presented as an example of an effort related to the measurement, evaluation, and utilization of skills data.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The use of 3D printers has been spreading in schools as well, and 3D printers were newly introduced in the revised Junior High School Course of Study Guidelines for Technology and Home Economics and the Guidelines for the Development of Teaching Materials. However, when using a 3D printer in class at school, there is a problem that it takes time to model the creation of all students. In this letter, Measure the modeling dimensions and the roundness of the corners when the scale of the model is changed, and consider the possibility of using it at school based on the obtained data.

Papermaking technique is implicit knowledge based on many years of experience of craftsmen. In this study, we investigate the factors that cause the weight of Japanese paper to vary depending on the papermaking conditions. The subjects of the survey are the measurement of the movement of the "suketa". The movement of the "suketa" is measured using a motion sensor. The measurement results suggest that the craftmen adjust the choushimizu time.

Feedback control, which is said to originate from a speed governor that controls the rotation of a steam engine, is widely used. However, the effect of the feedback control may be difficult to understand for beginner. This paper reports the results of developing teaching materials that show how feedback control improves control performance compared to simple ON-OFF control.

The purpose of this paper is to estimate the manufacturing-related variation factor from the difference in variance and correlation of the high-precision physical model parameters for a miniature triode vacuum tube 5751 with an amplification factor of 70. The vacuum tube operating model used here is based on physical equations adapted to the large signal input behavior of vacuum tubes used in guitar amplifiers and incorporates the effect of modulation of the amplification factor. This improves the accuracy of the soft clipping and hard clipping characteristics that affect the spectrum of the distortion sound. In order to improve the accuracy of the extraction of such multivariate model parameters, we devised a new analytical formula. In addition, we devised an algorithm for sequential regression analysis of the simulated and measured values against the analytical equation, and all parameter extraction was performed automatically by a computer program. As a result, correlations between the parameters, which had not been found before, were confirmed, and it became clear that the manufacturing and assembly accuracy of the grid electrode strongly affected most of the physical parameters.

A parcel delivery method combining a vehicle and a drone is proposed. In a parcel delivery business where delivery time windows exist, the delivery order is determined by considering both keeping the delivery time windows restriction and shorting the total delivery time. To solve this problem, firstly, an initial solution is obtained by looking ahead multiple route candidates and selecting the point that leads to the route with the largest number of packages that can be delivered during the specified time windows as the next destination. Then, the initial plan is successively improved. Through simulation evaluation, it is confirmed that the proposed method can increase the number of packages that can be delivered during the specified time windows and reduce delivery time compared to a method where an initial solution is greedily searched by using only next destinations' information.

In designing database-driven PID control systems, the offline learning scheme of PID gains included in the database has been proposed. However, it is difficult to apply this conventional scheme to real systems with unknown time-delays. In this study, a design method of database-driven PID controller using the response prediction is newly proposed. Plural databases are prepared corresponding to different time-delays and rise times. Furthermore, data-driven response predictive method is also introduced to predict responses and time-delays for each databases. As a result, the database with the desired control performance for the controlled object is adopted. The effectiveness of the proposed scheme for unknown time-delay systems is numerically verified in simulation examples.

In this paper, MOEA/D is extended to constrained optimization by making the constraints an objective function. An adaptive adjustment method is proposed to introduce a parameter for varying weights. The parameter for varying the weights is given in such a way that the bias of the search towards the feasible and infeasible regions can be adjusted. The parameter is tuned based on two guidelines to properly utilize infeasible solutions. The first is actively utilizing infeasible solutions with large constraint violations and encouraging global search including the infeasible regions. The second is actively utilizing infeasible solutions with small constraint violations and encouraging a search on the boundary of the feasible regions. This is expected to improve the global optimization performance to the feasible regions, which is a non-convex set, and the convergence performance to feasible solutions. We verify the usefulness of the proposed method for problems where the feasible regions are a convex set and a nonconvex set.

It is proposed to incorporate 1DCAE into a virtual engineering system in mechanical system design. In order to continue using an established virtual engineering system for a long time, it is necessary to modify it in line with the evolution of CAD, CAE, analysis, and evaluation technologies. If information in CAD or the like is coded directly in the system, it will be necessary to make changes to the system. Meanwhile, if the evaluation method, etc. is changed, the user interface of the system may need to be changed. These changes require software engineers and are costly and time-consuming.

In this paper, we propose that the elements in the system be independent, that the relationship between each element be defined by JSM, and that 3D-CAD be used for user interfaces. This will allow even those without software language skills to update the technology and create a long-lasting virtual engineering environment.

Electric potential therapy is widely used as a home-healthcare apparatus to treat ailments such as insomnia. However, the mechanisms for its effects remain largely unknown. This study aims to investigate effect of electric potential therapy on cortisol and axillary temperature. For this purpose, healthy males participated in the experiment, receiving 60 minutes of electric potential therapy. During the therapy, the concentration of cortisol in saliva was measured every 20 minutes. Axillary temperature was measured before and after the therapy. Results of statistical tests indicated a significant decrease of cortisol concentration during the therapy and a significant increase of the temperature after the therapy.