論文

Sampling periods in digital control systems have been shortened thanks to the development of both hardware and software technologies. In recent years, FPGA (Field Programmable Gate Array) has been applied to robot systems to achieve hard real-time system with short sampling periods. Due to the short sampling periods, the effect of the time quantization has been reduced. Some other hardware restrictions, however, become critical issue. In this paper, current dynamics in motor driver is considered as the hardware restriction. The current response dynamics acts as a low-pass filter, and it can be the restrictions of performance improvement. In the proposed method, the dynamics is modeled as low-pass filter, and the modeled dynamics is compensated by a phase-lead compensator. The tracking performance in an acceleration control system is improved by the proposed method. The effectiveness of the proposed method is validated through simulations and experimental results.

This paper describes with the design of a communication network necessary for Demand Response systems adapted to the requirements of the Japanese power grid. Based on KNIVES controllers and network devices an exemplary redundant hierarchical tree structure is proposed to meet high demands on reliability, scalability and dynamic adaptability in order to be capable to secure the wholesale competition. Therefore essential information for energy management has to be secured, managed, processed and delivered. Using Internet for communication, the network has to guarantee reliability facing a high variety of network availability. This approach focuses on redundant data management combined with non local control loops of the power supply system, which shall guarantee a functional safe and high-performance microglia. © 2006 IEEE.

Extending Content Delivery Network (CDN) infrastructure that has features of router-based network management system (RNMS) is highly appealing and challenging. It allows developing a CDN architecture based upon standard design to ease interoperability, scalability, performance, and flexibility both on network monitoring and management controlled from a router. To better understand the system model, necessity, and the advantages of RNMS, this paper proposed an algorithm that distributed in to a special router called Service-oriented Router (SoR). The function of algorithm is to manage the effective and efficient number of replica server runs in the network. In CDN, minimizing the number of activated replica servers should be considered in order to reduce the operation cost of the system. We propose a semantic approached algorithm that has function to optimize the selection of active replica servers which managed from SoR. The algorithm has capability to find the best location of replica servers and performs load balancing among replica servers. Our simulation result indicates that the proposed algorithm can efficiently activate the replica servers according to user's request with 33.9% effective compared to other algorithm within about one millisecond RTT increase. © 2013 IEEE.

Insect-based bioconversion is an emerging and economically viable approach that could simultaneously solve the global issues on food waste treatment and protein shortage. An essence of insect-based bioconversion is to feed insects on food wastes and then harvest and refine the developed insects into value-added commodities. This is a circular bioeconomic approach that can efficiently upcycle the nutrients and energy in food waste streams back into agricultural supply chains, but the difficulty is how to realize mass production of insects. This paper reports a commercial-scale insect-based bioconversion system using black soldier flies, whose design and development follow a digital twin paradigm. In particular, an industrialized rearing environment has been established, where the larvae growth can be systematically monitored, controlled, and managed to evaluate the overall bioconversion process efficacy. The system has been deployed in a pilot plant, whose Phase I is capable of handling 20 tons of food waste feedstocks per day and has been consecutively operating to date.

Smart cities use cutting-edge technologies to monitor the real world and improve various aspects of human life, such as traffic, agriculture, electric power grid, and medical care. However, protecting users' privacy is crucial in smart-city applications for service coordination. Any leakage of users' sensitive information may prevent users from sharing their data, and thereby hinder the progress of smart cities. Differential privacy (DP) is one of the approaches that protects sensitive information in a dataset, and strongly resists background knowledge attacks. This study proposes a central differential privacy scheme using secure computing methods. After receiving the ciphertext of the data, the central data curator in this system generates a perturbed dataset in the encrypted domain. The unmodified data of each user is not exposed to the data curator, therefore the data users do not need a trusted data curator. Moreover, compared with the existing models in which significant amount of noise is locally added before sending the data to the data curator, the proposed scheme adds considerably less noise while maintaining the same privacy requirement, resulting in enhanced data utility. Model evaluation demonstrates that our system effectively protects the privacy of individuals and provides accurate data for statistical analysis.

For the future application-friendly Internet, we have presented a router architecture that enables to interact with a variety of rich services. The proposed router snoops a traffic data stream, inspects the packet payload as well as packet headers, and stores the designated data in the associated database. The service-friendly router uses the technology of DPI (Deep Packet Inspection) for enriching services. For this purpose, high-throughput regular expression processing becomes a crucial component embedded in the router in order to extract the required information from traffic streams. Moreover, target patterns of the regular expression processing can be dynamically and frequently updated according to the applications requests. In this paper, we mainly focus on the design and evaluation of the high-throughput regularexpression processor. It accelerates the processing performance of OR matching (pipe(\)-based matching) that is familiar in various emerging applications of future Internet. The proposed regular-expression processor achieves a low overhead processing under the condition that the updates of the regularexpression patterns are frequently issued. Evaluation results show that the proposed processor achieves 6.0-Gbps throughput of regular-expression matching when using 45nm standard cell library. © 2010 IEEE.

Network Management System (NMS) plays an important role in networks to maintain the best performance of a network. It employs variety of tools, applications, and devices in order to support network administrators to monitor and maintain the stability of a network. Fault management is part where the NMS dealing with problems and failures, such as congestion, in the network. Generally, most NMSs use Simple Network Management Protocol (SNMP) to monitor and map network availability, performance, and error rates. In the existing NMS process, an SNMP agent is deployed to get information about the network condition and then send them to the administrator for taking further action on solving the problems. However, deploying such agent to the network may increase the traffic density. On the other hand, packet latency and RTT will increase as well. In this paper, we implemented a prototype of the proposing novel system that no need to deploy such agent to obtain network information. Our system analyze the streaming traffic by implementing a Service-oriented Router (SoR). Our objective is to predict a congestion in the specific link in the network through a router-based data traffic analysis using a Bayesian network model. The purpose of the prediction is to support the network administrator to notify the early warning regarding to the fault in the network as long as possible before it actually happening. By this prediction, the network administrator can immediately taking action to avoid the problems.We provided simulation experiment to demonstrate the performance of the proposed system. Our simulation results show that the proposed system can predict a congestion link caused by a particular problem, before hand it is getting congested. © 2014 IEEE.

To cope with global energy-related problems, the effective use of renewable energy such as photovoltaic and wind power is required. As these energy sources are unstable, it is required to introduce batteries into the power grids. Vehicle to grid (V2G) is a technology that is receiving much attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, we constructed an EMS model using MATLAB/Simulink and determined the optimized capacity of the fixed batteries and EVs based on data sampled at an experimental site in terms of capital cost. Fixed batteries as well as EV batteries were modeled and evaluated using the actual parameters and constraints of the terminal. The main aim was to level the received energy and achieve the recharge level of the battery in one day to maintain a long battery lifetime. Through simulations, we determined the optimized capacity based on actually measured data. We could exploit the management method by considering the relation between fixed batteries and EV batteries. Using this relation, the proposed method could predict the optimized fixed or EV batteries capacity required. © 2011 IEEE.

This paper proposes a novel method of velocity measurement for motor drives with optical encoders. Acceleration control is indispensable for advanced motion control while it requires accurate velocity information. Although many methods on velocity measurement have been proposed, accurate measurement was not achieved in a high-speed range. We therefore propose " synchronousmeasurement method (S method)" that measures the velocity synchronized with alteration of pulse numbers. Accurate velocity measurement is achieved in all speed ranges with this method. Furthermore, other estimation methods are applicable in addition since the method does not require any model of a control object. Simulation and experimental results verify the validity of the proposed method. © 2005 IEEE.

With increasing attention to the secondary use of data, privacy protection laws such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have come into force to protect residents from unauthorized exploitation of personal data. Flow management is an effective method to track the distribution of user data in a multi-domain network environment. Transparency in the relationship between data and service providers is essential to track the status of data provision. Vendor and Consumer Relationship Management (VCRM) manages this relationship by regulating relevant flow information. VCRM is expected to collaborate with the edge-computing environment in the management of regional unit flow, wherein all access to personal user data should be restricted in accordance with the stakeholders' requests. Accordingly, this study proposes a packet processing function that collaborates with VCRM to manage the access control of flows passing through a regional network. Moreover, this paper proposes methods to reduce packet processing time on the switch, and requests to the switch controller. Using tag-based matching and cache injection methods, the number of requests to the controller decreased to 33.4% of the original figure. Our proposed method also reduces the total processing time on flow management switches in the network environment in the analysis of encrypted TCP streams such as HTTP over TLS and MQTT over TLS. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Recently, there has been high demand for an efficient energy management system that decreases total energy consumption. The Great East Japan Earthquake of March 2011 resulted in the shutdown of nuclear power plants in Japan, thus limiting the supply of power. Since then, the need for an energy management system has become more pronounced in Japan. Such a situation warrants efficient energy consumption through the use of an energy management system. When heating, ventilation, and air conditioning are restricted, especially under peak-cut or peak-leveling control of electric power consumption, it should be ensured that the living environment is not uncomfortable for humans. However, in the existing methods, living environment comfort has not been considered practically in terms of the fundamental parameters, namely, volume, window size, and number of people in a given room, despite the considerable influence of these parameters on room amenity. In this study, we proposed a new control method that considers these parameters for maintaining the amenity index in indoor environments at a set value by predicting the predicted mean vote value. Furthermore, we set up a building energy management system in an office building in Kanagawa, Japan, to compare the proposed control method with an existing one. Two different cases were considered in this experiment: control using an existing method and control using the proposed method. The results show that the proposed method maintains the amenity index of the room at the desired level, while reducing peak and total power consumption levels. © 2013 IEEE.

© 2015 IEEE. In a data center, the main challenge is dealing with the power consumption of IT equipment and air conditioning (AC) units. To reduce the total energy in a data center, many techniques and approaches have been proposed. These strategies focused on the idle power of servers or controlling AC units while considering the temperature of server racks independently. In this paper, an active controlled shutter that enables the control of cooling airflow was proposed while considering the temperature of servers independently. By using the proposed method, wasted cooling energy could be eliminated. In a simulation of the proposed method, a conventional task assignment method was used, and start-up delays were considered. Additionally, the effect of the active controlled shutter was evaluated. The shutter blocks off cool air from cold aisles by observing the temperature of a server. As a result, the cooling power of the AC can be reduced by preventing the excessive cooling of idle or shut-down servers. An experimental result shows that the proposed method reduced the cooling energy by 22.8 %.

© 2015 IEEE. In this paper, an effective low-cost heating, ventilation, and air conditioning (HVAC) control system incorporating a new sensor is proposed. This research builds upon our previous system, which achieved efficient control of the air conditioning (AC) for a large room in a library. By detecting whether or not individual chairs were occupied and regulating the AC near unoccupied chairs, the system reduced the overall power consumption. This detection was achieved using pressure sensors installed in the chairs. However, the sensors required battery power to measure voltage and transmit data. The batteries needed to be replaced within several months, and thus the system required frequent maintenance. In this paper, we introduce a self-powered sensor. The sensor integrates an energy-harvesting switch and a wireless transmitter. The action of pressing or releasing the switch generates sufficient electricity to power the device, and this enables long-term operation without replacing or charging the batteries. When these sensors are integrated into chairs, occupancy status can be detected without additional power or regular maintenance. The proposed improved system with battery-free chair sensors is evaluated in an eight-day experiment conducted at a library in Kurihara, Miyagi Prefecture, Japan. The energy efficiency evaluation indicates that the proposed system can reduce electricity consumption by 18.3%. The predicted mean vote (PMV) values for the environment in the library are determined to assess the comfort level, and these values confirm that the proposed system is capable of maintaining occupant comfort. In the experiment, wireless sensor network is built through the Library to the Laboratory. All sensing data (e.g. temperature, humidity occupancy, status, power consumption, air conditioning status) are managed on the Cloud.

the field of motion control, robustness is an important issue to accomplish desired motion of robots. To achieve robust motion control, acceleration control has been studied. In the acceleration control, disturbance observer is used to estimate and compensate disturbance force applied to an actuator. In the disturbance observer, the disturbance is estimated with calculating acceleration based on velocity/position information, and the estimated disturbance is obtained through a low-pass filter. To achieve accurate disturbance estimation, higher cut-off frequency of the low-pass filter and exact acceleration information are required. To set higher cut-off frequency of the low-pass filter, shortening sampling period is an effective method using FPGA as a motion control processor. However, short sampling period generally deteriorates the resolution of the velocity/acceleration information. This means that the estimated disturbance can include large error. In this paper, an acceleration estimation method is proposed to improve the resolution of acceleration in systems whose sampling period is very short. The validity of the proposed method is demonstrated by simulation and experimental results. © 2008 IEEE.

FPGAs are focused on recently as motion control processors. Sampling periods become shorter by using FPGAs, and it is expected that improvement of the performance of the motion control system. However in M method, which is the most generally used velocity estimation method, velocity resolution becomes low due to the short sampling period. This leads to a limitation of the performance, especially in acceleration control using a disturbance observer which requires accurate velocity information. There are several velocity estimation methods to improve the resolution. These methods require a dividing operation. From point of view of resource sharing and resource utilization of FPGAs, implementing divider is not desired. In this paper, velocity estimation which does not require any divider is proposed to improve the velocity resolution in the short sampling period system. The validity of the proposed method is demonstrated by simulation, and the proposed method is implemented into position control system based on the acceleration control in experiments. ©2007 IEEE.

© 2016 IEEE. In a smart city infrastructure, Wireless Sensor Network (WSN) is the most important technique to collect environmental data to provide services. WSN becomes more and more popular research area because of its usefulness and huge demand. Since energy resource in WSN is limited, the design of a WSN system should consider energy effectiveness as well as fulfilling application requirements. The effectiveness of the system totally depends on its application and hardware specifications; thus, the routing algorithm of WSN must be optimized to achieve the energy effective communication. The proposed algorithm Energy Consumption-oriented Route Selection (ECORS) is the route selection algorithm attempting to prolong the system lifetime, especially for data collection application. In this paper, the suitable mechanism for data collection is proposed with focusing on implementation, which includes the actual packet transactions mechanism and the improved function for selecting routes in an assumed environment. By modifying the parameters with the thought of implementation, proposed mechanism can extend the lifetime 2.03 times longer than the fixed routing scenario. Furthermore, the simulation result is analyzed in detail with focusing on state of charge variation on each node. Moreover, the new indicator to depict the relationship between lifetime expansion rate and parameters used for the algorithm is introduced. By using this indicator, lifetime expansion rate can be assumed without simulation, which is helpful for implementation.

© 2017 IEEE. Recent trends in the applications of batteries in the built environment are improving the efficiency of batteries and lowering costs. This paper introduces various types of battery technologies such as sodium sulfur, lithium ion, flow and lead acid batteries and discusses their models. Various applications of batteries such as adaptive battery systems, Battery Electrical Vehicles (BEVs), Battery Energy Storage Systems (BESS), the Internet of Things (IoT), and Smart Grid and Smart Environment applications are also discussed. In their selection and use of batteries, scholars are ultimately looking to maximize occupant comfort whilst keeping costs low and optimizing the energy efficiency of buildings. This paper will provide a review of current trends in this field.

Due to increasing secondary use of data, recommender systems using anonymized data are in demand. However, implementing a recommender system requires complicated data processing and programming, and the relationship between anonymization level and recommendation quality has not been investigated. Therefore, this study proposes a framework that facilitates the development of recommender systems. Additionally, a method is proposed for quantitatively evaluating recommendation quality when the anonymization level is varied. The proposed method promotes data utilization by recommender systems and determination of compensation for providing data based on anonymization level. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

In recent years, there have been rapid increases in the number of network-connected devices such as computers, smartphones, and Internet of Things devices. Thus, large amounts of data have been accumulated such as locational data, website search histories, and power usage data. These data are used in various types of services. However, these data cannot he used easily for secondary purposes in some countries because of privacy problems. Therefore, privacy protection is necessary to apply these data in secondary uses where data anonymization is the usual solution. Many conventional methods are used for anonymizing power usage data, but the conventional method has three problems. First, it cannot anonymize time-series data. Second, the information loss is so large in the conventional method that the anonymized data are no longer suitable for secondary uses. Third, the conventional method cannot preserve the type of electrical appliance used. In this study, we propose a method for anonymizing power demand data, where sparse coding is used to solve the three problems that affect the conventional method. The proposed method can anonymize time series-data and it allows data to be analyzed at a chosen time. The proposed method was used to anonymize power usage data from the Urban Design Center Misono (UDCMi) and the experimental error rate decreased compared with the conventional method. The dictionary produced using the proposed method represents the electrical appliance data.