This paper discusses about measurement and control technology for Life innovation. In Technical committee on Control Engineering, there are two committees which treat measurement and control technology associated with Life innovation. Since these committees started, several interesting research topics about Life innovation are proposed in technical meeting, so we introduce these research topics.
Auscultation is one of the essential skills for clinical examination, in particular, of the respiratory system. Sparse modeling is one innovative technology for discovering components of biological signals including auscultatory signals, of which characteristics and irregurity can be interpreted as redundancy or sparsity of their features. This article explains and demonstrates how to apply the sparse modeling techniques to biological signals, showing lung sound separation as an example.
Compared with Si-IGBT, SiC-MOSFET is expected to reduce switching loss and conduction loss of the low current region, and also to remove external freewheeling diode. It is generally known that SiC-MOSFET body diode has a small reverse recovery charge, nevertheless it can generates large loss depending on operating condition because of pin diode structure. It has been reported that the reverse recovery charge of pin diode could be reduced by shortening diode conduction time for Si devices, however the effect on SiC-MOSFET body diode has not yet become clear. This work clarifies the effect of shortening diode conduction time in reducing reverse recovery charge of SiC-MOSFET body diode. It was confirmed that when the diode conduction time was shortened to 60 ns, the reverse recovery charge of SiC-MOSFET body diode could be reduced by approximately 60%.
Normally, thermal breakdown is one of the serious failure phenomena in the power device application, which drives the researchers to focus on exploration of the failure mechanism and the new evaluation method for power device. In this paper, unclamped inductive switching (UIS) test is presented to evaluate energy handing ability and maximum junction temperature of 1200V/19A SiC MOSFET during avalanche mode. It is verified that commercial 1200V/19A SiC MOSFET can easily withstand almost ten microseconds avalanche time and around 924 K maximum junction temperature with 1 mH inductance and 400 V DC bus at the case temperature of 300 K in avalanche mode. In addition, three reasonable evaluation methods of the maximum junction temperature for SiC MOSFET are summarized at different case temperatures.
We propose a redundant successive approximation resister (SAR) ADC design method using an SAR search algorithm with a silver ratio (meaning square root of 2). This enables high-speed AD conversion using digital error correction. We show that this method can realize high speed SAR AD conversion when taking account into the internal DAC incomplete settling and using two clocks of different periods. We also present that its control circuit can be designed with simple structure.
In this paper, a synthesis of a doubly RC terminated RC polyphase filter is proposed. The terminating circuits on both sides are composed of resistors and capacitors connected in parallel. Especially, in many cases, the terminating circuit at the load side becomes an equivalent circuit of the following building blocks such as MOS amplifiers. It is described that the transfer response of the proposed circuit becomes the same as that of the conational one. The proposed circuit is obtained through the coefficient matching method in the same as the conventional polyphase filter. In addition, the RC-parallel circuit at the source side is approximately modified to the RC-series one in order to take the source resistance included in the voltage source into account. As an example, a third-order doubly RC terminated RC polyphase filter and its approximately modified one are designed. The validity of the proposed method is confirmed through computer simulation and experiment.
This paper presents an earbud-based photoplethysmography (PPG) and its application. This PPG recording system permits long-term continuous monitoring of cardiovascular function since it can be worn comfortably on ears. Experimental investigations showed that stress and drowsiness could be estimated by analyzing measured PPG signals. Furthermore, noise suppression techniques for motion noises and ambient light interferences are introduced to make a recorded signal more acceptable.
A single or multiple kinds of internal or external environmental variations of the system often cause the property variation of any system under control, and the readjustment of controller parameters is required. To maintain high performance of controlling and minimize the total cost for readjustments of the controller parameters, determination the appropriate timing for readjustment the controller parameters is important. This paper proposes new procedure to determine the appropriate timing for the readjustments based on the time-series data using the recurrent neural networks (RNNs). A well coordinated RNN with proper structure has high performance on the predication of time-series data with the assistance of its internal signal feedback structure. This paper conducts some numerical experiments to verify the availability of the proposed method to some systems. The experimental result indicates that the proposed method has higher performance than other existing method with the same aim.
It is said to be coming the era of "Internet of things" (IoT). In this field, various things connect to the network. In addition, the using of IoT is rapidly becoming the most popular concepts in the industry of Factory Automation and Control System Management. IoT concept makes a new opportunity on analyzing and intelligent component packages. However, the IoT concept caused the problem of the management for consistent identifiers. To solve this problem, we propose two techniques. The first technique is "Structured ID" that is able to define complicated structure of control systems using IDs on tree structure. The second technique is "Relational link" that is able to describe meaning for subset of structured IDs. Our proposal techniques reduced the development cost of control system manager to 1/3. Additionally, we are providing two products using these techniques.
Proportional-integral-derivative (PID) control is an effective approach in process systems such as petroleum plants and chemical plants. Actually, PID controllers have been employed for more than 80% of real systems in process industries. When a PID controller is employed, determined PID parameters strongly affect control performance. Therefore, lots of tuning schemes for PID parameters have been proposed. Moreover, much knowhow has been in industries. However, according to the internal model principle, PID controllers do not work effectively to systems with periodic disturbance. Therefore, some defective products are produced and it may be a waste of resource. The products can be reduced by using advanced controllers. However, advanced controllers are not employed widely because the knowhow of operators to tune PID parameters cannot be applied. Furthermore, it is important to employ research results widely for green innovation. Therefore, it is required to suggest an advanced control method that can be applied with their knowhow. In this paper, the generalized minimum variance control (GMVC) is applied to remove the influence of periodic disturbance. The GMVC controller has the internal model of the periodic disturbance. Then, the augmented system constructed by GMVC is designed so that the system has the same characteristics of the controlled object. Moreover, a PID controller is designed to the augmented system. As a result, the operator can regard the controlled object as the system without periodic disturbance, and the conventional tuning knowhow can be employed to the PID controller. The effectiveness of the proposed method is evaluated by a numerical simulation example.
This paper reports an estimation result of thermal conductivity and thermal expansion coefficient for insulating firebrick model with radiation from heating furnace. The insulating firebrick is used for blast furnace in steel industry and exposed to high temperature environment. In this situation, it is difficult to specify physical characteristics such as thermal conductivity and thermal expansion coefficient because the measurement methods regulate allowable measurement ranges for temperature. Moreover the physical characteristics change as time passes. That is, the estimation of physical characteristics is essential to model the dynamics and keep the control performance considering active safety. It also indicates that the characteristic of the model obtained by the estimation becomes the basis of green innovation. Therefore, this paper models an insulating firebrick with radiation from heating furnace and tries to estimate thermal conductivity and thermal expansion coefficient through extended Kalman filter and experimental data. From the result, it found that the physical characteristics could be estimated by the input and the output data about insulating firebrick.
This paper considers the positioning of a pneumatic stage. To achieve high precision positioning under different length of pipe, which connects servo valves and cylinders, a pneumatic system is divided into two subsystems. In this situation, model following control (MFC) is employed so as to compensate effects of unknown parameter of the pneumatic system. Experiments demonstrate that, by using the MFC, the repeatability of positioning is improved.
In this paper, the stability condition and the robust performance condition are represented as a set of convex constraints with respect to the parameters of a linearly parameterized multivariable controller in the Nyquist diagram for the prespecified frequency points. This method can directly handle frequency-domain additive uncertainty without any modeling. Frequency-domain additive uncertainty can be minimized by appropriately selecting a nominal plant at each frequency point in the proposed approach. Moreover, this paper proposes the design constraints to assure the desired control bandwidth, phase margin and gain margin to satisfy desired control specifications. The effectiveness of the proposed method is verified by comparison with the model-based approach by using µ-synthesis with the D-K iteration algorithm and the case of the designed controller without proposed constraints through an experimental result.
A Japanese novelist Keiichiro Hirano proposes a concept of dividual to explain interaction between humans. This paper models the dividual using three machine learning techniques and develops a new human-robot interaction system using the proposed dividual model. The system consists of two parts; dividual identification and action selection. In the dividual identification, the system recognizes the person who interacts with and learns about him/her through the interaction using self-organizing map. In the action selection, the system selects an action using a Bayesian network whose conditional probability table is updated by Q-learning. Through computer simulations, it is verified that the proposed dividual model can select an appropriate dividual for the specific person to be interacted with. It is also shown that the dividual model can suggest an appropriate topic according to the specific person.
We propose a methodology for pointing-gesture detection using background subtraction that is robust to small changes in the background. We have developed an interface system that enables the user to input and obtain information in a position-free manner within a specific area of the environment using a projector-camera system. The system projects a command dialog box and observes the button that the user points at with their fingertip and thus receives commands. To detect the pointing gesture, the system extracts the hand region using background subtraction and detects the fingertip position based on the convex hull of the hand. We studied a background subtraction methodology that does not require a model of the background changes in advance. First, phase-only correlation is used to align positions between the input image and the background image. Then, similarities calculated from three features; local binary patterns, fractal dimension and color, are integrated into a unified similarity by Choquet integral. Noise is removed using a temporal weighing map representing the possibility that a pixel is in the foreground. The system discriminates foreground from background using similarity thresholding. We experimentally validated the proposed methodology for detecting pointing gestures.
This paper discusses a method to detect electroencephalogram (EEG) patterns using a self-organizing map (SOM) based on a learning algorithm for plural-attribute information (SOMPA). The input data for SOMPA has two attributes which are EEG feature and individual feature. We set the EEG feature to main feature and individual feature to sub-attribute information. The winning node in the learning algorithm of SOMPA is determined by using main feature and sub-attribute information. In the preprocessing, we extract the EEG feature vector by calculating the time average on each frequency band which are θ, α and β, respectively. The individual feature is analyzed though the ego analysis using psychological testing. In order to prove the effectiveness of the proposed method, we conduct experiments using real EEG data. The experimental results show that the EEG pattern detection accuracy using SOMPA improves compared with the standard SOM.
Modern society has seen a tremendous growth in the amount of digital data, however a database for human stress currently is not prevalent. Additionally, diagnostic criteria based on evidence, quantitative scales have not been fully established for stress. The purpose of this research is to provide visually presentation method of stress evidence paper in conjunction with web article in order to help people understand and overcome their stress. We propose a stress evidence search engine named “Kokoronoma” incorporated with i) a rate of evidence which express the relationship between the web article and the scientific paper, ii) human machine interface to show the rate of evidence visually. The fabricated stress evidence search engine was evaluated by the 10 young male users to compare with a multipurpose search engine as Google and Google Scholar. Three kinds of search problem as serotonin, mood disorder, and depression were used for the evaluation. As the results, Stress evidence paper and the rate of evidence were showed in conjunction with web article, automatically. The scores of subjective evaluation of the stress evidence search engine for visible observation images, intuitive awareness, and un-complicatedness showed higher than that of the multipurpose search engine. It was considered that the fabricated stress evidence search engine has an effective in reducing the stress of user.
While the LTE has been in widespread use and the line speed for data communications has also been improved, the exploding data traffic required by evolving applications is thought to increase the utilization factor of public WiFi services from now on. The throughput (TP) and the round trip time (RTT), however, might become longer for reasons of increasing heavy processing load on a public WiFi station or network load. On the other hand, the required TP or RTT are totally dependent on the application which a user is working on. This paper defines a degree of satisfaction of terminal that is the difference between the required TP or RTT for a user's application and the actual TP or RTT obtained when a mobile terminal gets connected to a station. The paper firstly formulates a problem to assign some mobile terminals with the different communications services by means of graph theory, and it also proposes a method to maximize the degree of satisfaction of terminal in the whole system with considering the required TP or RTT for user's applications based on a connection service determination logic by Hungarian method.
While variable renewable energy source, VRE, such as photovoltaic power, rapidly increases, concerns over the shortage of downward adjustment margin of conventional large-scale power generation facilities become patent. We propose a new type of demand response, named iDR, which mitigates curtailment of over-generation of VRE by embracing a large number of pieces of small IoT appliances with minute energy demand particle size through IoT technology. Our potential simulation shows that the iDR is able to substantially mitigate the curtailment of photovoltaic over-generation by dispatching power consumption to iDR appliances using iDR applications.
In the Internet, TCP is a wide commonly used transport layer protocol. However, the utilization of bandwidth of conventional TCP decreases in the high bandwidth. As one of mitigation measures, HighSpeed TCP has been proposed. However, the utilization of bandwidth of HighSpeed TCP decreases when the bandwidth of bottle-neck-link changes, because the recomended value of parameters of HighSpeed TCP are determined assuming packet size is 1,500 Bytes and line speed is 10 Gbps. In this letter, we propose a new congestion control method introducing learning automaton into HighSpeed TCP, aiming to adjust the important parameters of HighSpeed TCP adaptively.
A time-to-digital converter (TDC) based on stochastic process and statistics theory is presented. This architecture utilizes the stochastic variation in CMOS process positively for fine time resolution. It needs a large number of flip-flops for statistics but advanced fine CMOS technology can realize it. The self-calibration technique using the histogram method is applied to compensate the nonlinearity due to the circuit characteristics variation as well as timing skew by layout and routing. The proposed TDC can be implemented with full digital circuit, which is suitable as nano-CMOS mixed-signal circuit. Register-Transfer-Level (RTL) simulation is conducted to validate the operation principle. RTL verification results indicate that the proposed stochastic architecture with self-calibration feature can realize a linear TDC with sub-picosecond time resolution.
This paper describes an optimal shielding shape of elevator shafts for installations of MRI and Electron Beam Lithography System. The imaging of the MRI is mainly disturbed by the magnetic flux density fluctuations (MFDF) in the direction that the uniform flux is applied with amplitudes of 1.5 T and 3.0 T. Almost all MRIs are set horizontally, so the shielding method for the horizontal component of the MFDF was primarily investigated. A shielding shaft divided into upper and lower parts with a gap also enables the opening for going in and out from the elevator. Firstly, the MFDFs due to the movement of the elevator were measured. Then, the magnitudes and directions of the magnetic moments that can model the magnetic materials of the elevator were estimated using an inverse problem, so that the MFDFs obtained agree with those measured. Secondly, the relationship between shape of shielding shaft and the estimated fluctuations of leakage magnetic field in the horizontal and vertical directions due to the movement of the modeled elevator was investigated using a 3D finite linear magnetic-field analysis. Lastly, the optimum shape of the elevator-shielding shaft for preventing MFDFs due to the movement of the elevator was investigated by analysis.
Recently, a novel recording system is strongly required for agile and precise recording of biosignals in various fields, such as medicine, neuroscience, BMI (Brain Machine Interface), and so on. To enable such various biosignal recording, we have proposed an agile biosignal recording system with a newly designed analog front-end LSI chip having amplification, filtering, and A/D conversion functions. In this paper, we designed and evaluated a neural signal recording circuit and a portable front-end motherboard. The neural signal recording circuit chip and discrete ICs were mounted on the motherboard. We confirmed that our functional LNA (Low Noise Amplifier) had variable gains and cutoff frequencies appropriate for various biosignals, and also confirmed that biosignal recording board system successfully measured a human electrocardiogram.
Usually, outside air temperature of a house increases when we use air-conditioners because of exhaust heat from the outdoor units. Consequently, electrical consumption of the area increases because many people turn on the air-conditioner. Influence of this phenomenon depends on distances among each house and arrangement of the houses. Obviously, distance between each house becomes further, effect of exhaust heat gets weaker, but the distance cannot be extended easily in urban areas because of limited space. Thus, relationship between arrangement of houses with air-conditioners and electrical consumption in a target area is investigated. A house with an air-conditioner and an outdoor unit is represented as a mathematical model, and multi-agent simulations have been conducted with the model. Effective arrangements of houses and ineffective arrangements of houses have been found by using random search method, and the arrangements have been compared. It has become clear that electrical consumption decreases when houses with low preset temperature get closer with each other in built-up areas.