Two-dimensional variation of bursting properties in a silicon-neuron half-center oscillator.

We are developing hardware models of central pattern generators (CPGs) to enhance neural prostheses, create biologically based controllers for autonomous machines, and to better understand how biology creates stable and robust movements. Previously, we designed and implemented an analog integrated circuit model of a neuron with Hodgkin-Huxley like dynamics, the silicon neuron. In this work, we use silicon neurons to implement a half-center oscillator and show that the underlying dynamics of this CPG produce bursting behaviors that are well matched to the biological counterpart on which our model is based. In addition, we demonstrate the robustness of the bursting behavior by systematically varying two parameters in each silicon neuron and mapping the corresponding effects on the bursting.     

A neuron model with synaptic nonlinearities in a dendritic tree for liver disorders

With the number of deaths due to liver diseases increasing steadily in recent years, early detection and treatment of these diseases has been one of the most active research fields using computational intelligence techniques. In this paper, we propose a more realistic single‐neuron model with synaptic nonlinearities in a dendritic tree for liver disorder diagnosis. The computation on the neuron is performed as a combination of dimensional reduction and nonlinearity, which has a neuron‐pruning function that can remove useless synapses and dendrites during learning, forming a distinct synaptic and dendritic morphology. The nonlinear interactions in a dendrite tree are expressed using the Boolean logic AND (conjunction), OR (disjunction), and NOT (negation), which can be easily implemented in hardware. Furthermore, an error backpropagation (BP) algorithm is used to train the neuron model, and the performance is compared with a traditional BP neural network in terms of accuracy, sensitivity, and specificity. We use the BUPA liver disorder datasets obtained from the UCI Machine Learning Repository to verify the proposed method. Simulation results show promise for the use of this single‐neuron model as an effective pattern classification method in liver disorder diagnostics. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

On the capability of the T‐S model in describing nonlinear systems

The Takagi‐Sugeno (T‐S) model is one of the most powerful methods in describing nonlinear systems. Because the T‐S model can be easily converted into an LPV system, Lyapunov stability analysis and controller design reduce to solving an LMI problem. However, since the constructed T‐S model is generally approximation, how to construct a T‐S model with less approximation error is important. In this paper, we propose a modeling method for T‐S model which yields no error for some class of nonlinear systems, and discuss some expansion as well as estimation of error bound for general nonlinear systems. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 166(1): 52–59, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20503     

A modified nanoelectronic spiking neuron model

Spiking neural networks (SNNs) first came to the attention of scientists due to the search for a structure capable of emulating more closely the behavior of the human brain. The biological nervous system has some characteristics that allow it to process a large amount of data very quickly. It is also a fault-tolerant system, with a high level of parallelism. Low power consumption is another feature of the human brain that is desirable for electronic circuits. In this context, several models of artificial spiking neurons were developed, aiming to construct networks able to combine the best characteristics of the human brain. Most of these models, however, lack validation in larger networks. This paper proposes the implementation of an SNN based on a nanoelectronic spiking neuron model developed in previous works. To validate the behavior of an isolated neuron in a network, logic gates (NOT, OR, AND, and XOR) are used as a benchmark. The goal of this paper is to present a feasibility study on the possibility of implementing such nanoelectronic spiking neuron networks based on this spiking neuron model. Nanoelectronics represents an appealing implementation due to the gains regarding occupied area and power consumption, which are inherent characteristics of this technology. The neuron model was modified for simulation at room temperature. An information code based on the amplitude of the pulses presented at the output of the neuron was developed. During deployment of this approach, some limitations regarding the neuron model were detected; some possible solutions are proposed as future work.     

Robust damping control of power oscillation incorporating parametric resonance

In this paper we consider a damping control of low‐frequency oscillations in an electric power system. On the basis of the hypothesis that an auto‐parametric resonance model can explain a power oscillation, we propose a new model for a robust damping control, by which the system maintains stability even if some auto‐parametric resonance happens. With this model, we can express a parametric variation of a principal oscillation mode and a class of uncertainties which cover neglected dynamics. Since the model has a certain structure of uncertain parameters, we design a robust controller via µ‐synthesis. The robust controller which can be obtained from the presented design strategy has the property that the control performances are more sophisticated in comparison to controllers designed with other existing methods based on the H_∞ control. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 142(1): 42–49, 2003; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10069     

Information system development by business process modeling based on adaptability to specification changes

Business modeling has been attracting attention in the development of information systems to be used for analyzing and designing the working procedures of the system under development. In this paper, we propose a method of information system development by business process modeling based on adaptability to specification changes. The proposed method builds a business process model from the requirement specifications, translates the model into UML, identifies the elements bridging the translation from Business Process Modeling to UML, that is, the analytical stage and the design stage, and seeks to perform both processes continuously while finalizing the design. The proposed method was applied to the prototyping of a bus booking and management system, comparing the results using only UML for the configuration with those obtained by using the proposed method. The proposed method proved effective in the early detection and removal of bottlenecks, in accurate modeling, and in adjusting to changes in the specifications. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(2): 54–64, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21045     

A scheduled controller design of congestion control considering network resource constraints

In this paper, we consider a dynamical model of computer networks and derive a synthesis method for congestion control. First, we present a model of TCP/AQM (Transmission Control Protocol/Active Queue Management) as a dynamical model of computer networks. The dynamical model of TCP/AQM networks consists of models of TCP window size, queue length, and AQM mechanisms. Second, we propose to describe the dynamical model of TCP/AQM networks as linear systems with self‐scheduling parameters, which also depend on information delay. Here we focus on the constraints on the maximum queue length and TCP window size, which are the network resources in TCP/AQM networks. We derive TCP/AQM networks as the LPV system (linear parameter varying system) with information delay and self‐scheduling parameter. We design a memoryless state feedback controller of the LPV system based on a gain‐scheduling method. Finally, the effectiveness of the proposed method is evaluated by using MATLAB and the well‐known ns‐2 simulator (Network Simulator Version 2). © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 149(1): 61–68, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10341     

基于小波变换和神经网络的同步电机参数辨识新方法

准确地辨识同步电机参数,是研究分析电力系统运行和控制系统设计的前提。神经网络具有信号分离能力，但传统的人工神经元模型不适合分离同步电机的三相突然短路电流。为精确辨识同步电机的瞬态参数，文中提出了一种改进的人工神经元模型，并将小波变换和改进的线性人工神经元结合起来，对采集到的同步电机三相突然短路电流进行分析处理。利用小波变换对短路电流进行预处理，并辨识得到各个时间常数；根据辨识得到的时间常数来设定神经元激发函数中时间常数的迭代初始值，用改进的人工神经元模型对短路电流进行分离，得到其中的直流、基波和二次谐波电流分量，通过简单代数运算便得到电机的瞬态参数。仿真分析和实机试验表明，该方法能够有效地分离出短路电流中的信号成分，并且提高了电机参数的辨识精度。     

Optimization of multiobjective system reliability design using FLC controlled GA

A practical optimal reliability design of a system requiring high system reliability could be formulated as an appropriate mathematical programming model; however, in the real world, we should be concerned with some kinds of decision criteria. In particular, system reliability and construction cost are basically in conflict with each other, so that when taking both of them into consideration, the system reliability design model can be formulated as a bi‐objective mathematical programming model. In this research, we consider a bi‐criteria redundant system reliability design problem which is optimized by selecting and assigning system components among different valuable candidates for constructing a series‐parallel redundant system. Such a problem is formulated as a bi‐criteria nonlinear integer programming (bi‐nIP) model. In the past decade, several researchers have developed many heuristic algorithms including genetic algorithms (GAs) for solving multi‐criteria system reliability optimization problems and obtained acceptable and satisfactory results. Unfortunately, the Pareto solutions obtained by solving a multi‐objective optimization problem using a GA cannot guarantee its quality, and the number of Pareto solutions obtained is sometimes small. In order to overcome such problems, we propose a hybrid genetic algorithm combined with a Fuzzy Logic Controller (FLC) and a local search technique to obtain as many Pareto solutions and as good as possible. The efficiency of the proposed method is demonstrated through comparative numerical experiments. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 158(3): 72–80, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20319     

The development of generator modeling techniques for multimode oscillations and study of generator H ∞ control design method for robust control

Modern electric power systems of Japan are characterized by high density, wide area coverage, and a complicated structure. Multimode oscillations occur in the generators connected to the systems. These oscillations represent a combination of high‐ and low‐frequency modes that occur between individual power systems and oscillations of other types, such as the SSR and cross‐compound machine oscillations, which are characteristic mode oscillations of generators. In this paper, we first construct a real model of the generator that realizes the multimode oscillations. Next, model reduction of this real model is carried out, and a design model to be used for the control design is constructed. The H ∞ control design based on the modern control theory is presented by using this design model, which implements the damping of power system oscillations and robust stabilization of other multiple modes. In conclusion, we confirm that the target parameters of the control design have been achieved. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(1): 42–52, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10253     

Feedback enlargement of stability radius by nondifferentiable optimization

In controller design of dynamical systems, it is desirable that the controllers guarantee the stability for not only nominal plants but also perturbed ones, because the plant models may have some uncertainties in their parameters. By this motivation, several studies for the robust controller design have been conducted. In this paper, a feedback controller design method is considered, which achieves enlarging the degree of robust stability for the linear SISO closed‐loop systems. Choosing stability radius for the plant parameters as the degree of robust stability, and regarding this as an object function, we formulated this maximization as an optimization problem with constraints coming from prescribed pole placement. The difficulty of this formulation is that while pole placements give linear constraints, the object function is not a smooth one, which calls for an optimization technique for nondifferentiable functions. To cope with this, we successfully used the bundle method. We show some numerical examples to illustrate our proposed design method. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 166(3): 55–61, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20623     

Proposal of a Hamming distance detector using neuron MOS transistors

A neuron MOS transistor has been proposed which operates more “intelligently” than a conventional MOS transistor. In this paper, we propose a Hamming distance detector with a large noise margin using the neuron MOS transistors. The proposed circuit accepts two bitstreams to be compared in parallel, and makes it possible to determine if the two bitstreams are identical (“exact match”) or if the Hamming distance between the two bitstreams is within a certain range (“near match”). Moreover, the “acceptable” range of the Hamming distance (in the case of “near match”) can be soft‐programmed. The operating characteristics of the circuit are also analyzed in detail. Furthermore, these analyses are fully confirmed by simulation using the circuit analysis program HSPICE. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(1): 44–51, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20223     

Decentralized adaptive backstepping stabilization of interconnected systems with input time delays in dynamic interactions

In this paper, we provide a solution to the problem by considering input time delays in dynamic interactions. Each local controller, designed simply on the basis of the model of each subsystem by using filtered transformation and standard backstepping technique, only employs local information to generate control signals. The robustness of decentralized adaptive controllers is established. It is shown that the designed decentralized adaptive backstepping controllers can globally stabilize the overall interconnected system asymptotically. The L₂ and L_∞ norms of the system outputs are also established as functions of design parameters. This implies that the transient system performance can be adjusted by choosing suitable design parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Design support system for coloring illustrations by using the colors preferred by a user as determined from the hue patterns of illustrations prepared by that user

We propose a new design support system that can color illustrations according to a person's color preferences that are determined on the basis of the color patterns used by the same person in his previous work. Recently, many design tools for promoting free design have been developed. However, preferences for various colors differ depending on individual taste. Therefore, a system that can automatically color various designs on the basis of human preference is required. In this study, we propose an automatic modeling system that can be used to model illustrations. To verify the effectiveness of the proposed system, we simulate a coloring design experiment to determine the color patterns preferred by test subjects by using various design data. By using the design data, we determine each subject's preferred color pattern, and send feedback on these individual color patterns in the proposed system. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 181(1): 19–27, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21283     

Anti‐windup synthesis for a model predictive control system

In this paper, an anti‐windup design problem for a model predictive control system is studied. The plant is assumed to be stable. First, we propose the structure of an output feedback model predictive controller with an anti‐windup compensator. Then we show a design method of the anti‐windup compensator that guarantees closed‐loop stability and improves the transient response. The design problem of the anti‐windup compensator is reduced to a linear matrix inequality (LMI) optimization problem. Further, it is shown that there always exists an anti‐windup compensator that ensures global asymptotic stability. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Sensorless controls of salient‐pole permanent magnet synchronous motors using extended electromotive force models

In this paper, we propose a new mathematical model for synchronous motors and a sensorless control method based on it. To control permanent magnet synchronous motors, knowledge of rotor position and velocity are necessary. Heretofore, expensive sensors have been used to detect rotor position information. Although many sensorless control methods based on the electromotive force (EMF) have been developed for non‐salient‐pole permanent magnet motors, they cannot be applied for salient‐pole motors without approximation because of complications in the mathematical model; this is turn may lead to problems of instability. To solve this problem, we propose an extended electromotive force model for synchronous motors. The proposed model has a simple structure, making position estimation possible without approximation. Experimental results show that the proposed model and method are valid. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 146(3): 55–64, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10257     

A basic study of defect inspection methods for ASIC manufacturing line (Second report: Inspection parameter dependence on yield and cleaning cycle)

The results of strict defect control include both the enhancement of manufacturing yield and increased delivery delay due to a drop in the machine operation rate. Therefore, defect inspection methods must be optimized for this trade‐off, especially for ASIC manufacturing. In the first paper, we proposed a new manufacturing model which treats not only inspection and the yield model, but also the workflow model. In this paper, we formulate the inspection parameter dependence on the manufacturing yield and the machine cleaning cycle, which may affect delivery time. By using the resulting formulas, factory engineers can obtain practical information for inspection parameter optimization. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(2): 53–62, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10328     

Emergence of opinion leaders based on agent model and its impact on stock prices

The development of information technology has made it possible to obtain large amounts of information easily. Thus it appears likely that the impact on a society of word‐of‐mouth information communication and the like has been growing. In this paper, we propose a model of the emergence of opinion leaders based on word of mouth in an artificial stock market. The process of emergence of opinion leaders and the impact of opinion leaders on stock prices are verified by simulation. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 177(2): 32–40, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21163     

Modeling of switching frequency instabilities in buck‐based DC–AC H‐bridge inverters

In this paper, the dynamical behavior of a full bridge DC–AC buck inverter controlled by fixed frequency and PWM is studied. After showing that the system can undergo both period‐doubling and Neimark–Sacker bifurcation at the fast scale (switching period) by using the exact switching model, an exact solution discrete‐time model able to predict both instability phenomena is derived. The model is obtained without making the quasi‐static approximation and it can be used to obtain the useful operation region in the multi‐dimensional design parameter space from time domain simulations in a very fast and accurate manner. Based on the study of the system, some design guidelines are provided. Copyright © 2010 John Wiley & Sons, Ltd.