A sensorless brushless dc motor system

This paper describes a brushless dc motor system without position or speed sensor. The brushless motor consists of a permanent magnet synchronous motor and a voltage-source inverter capable of controlling the amplitude and frequency of voltage. The rectangular-shaped stator current with a conducting interval of 120° (electrical) is controlled to be in phase with the trapezoidal back electromotive force. This results in producing maximum torque. Variable speed is achieved by adjusting the average motor voltage similarly to chopper control of dc motors. In this paper, two sensorless position detecting methods, i.e., an “indirect method” suited for the lower-speed range and a “direct method” suited for the higher-speed range are proposed. The combination of the two makes it possible to detect the rotor position over a wide-speed range. Furthermore, a speed-sen-sorless PLL control is proposed in applying the principle of the direct method. Experimental results obtained from a prototype brushless dc motor are shown to confirm the validity of the sensorless drive. The starting procedure of the motor also is discussed because it is impossible to detect the rotor position at a standstill.     

Simulation study of eutrophication in Hiroshima Bay: Simulation of particulate and dissolved organic matter using cyclic transformation of carbon

A phytoplankton model, which includes a carbon cycle combined with a constant current obtained by the computation of tidal currents, was applied to the coastal region (Hiroshima Bay, Japan). The transformation rate constants for the carbon cycle were experimentally evaluated.The seasonal variations of particulate and dissolved organic matter by the simulation model were reasonably consistent with the field data. Carbon concentration increased by primary production in the upper layer was approx. 10 times that augmented by loading of carbon from land at the shore in summer. Sinking plays an important role in the elimination of particulate organic matter. On the other hand, horizontal advection and turbulent diffusion are important factors for the diminution of dissolved organic matter.     

Quantitative structural analysis of twin boundary in alpha-Zn7Sb2O12 using HAADF STEM method

The structure and composition of the 1/4{110} twin boundary in alpha-Zn7Sb2O12 have been determined by using quantitative high-angle annular dark field scanning transmission electron microscopy (HAADF STEM) analysis. The noise in the experimental HAADF STEM images is reduced by using the maximum entropy method and average processing, and the parameters used in dynamical simulations are experimentally determined. From the analysis, it has been found that octahedral sites in the twin boundary slightly shift parallel to the [110] direction, and a reduction of the Sb concentration at the octahedral sites on the plane adjacent to the twin boundary was detected. The reduction was measured from three regions in the same twin boundary, and the Sb concentrations were 4 +/- 3, 8 +/- 3 and 19 +/-2 at% from 33 at%.     

Development of a pulse control-type MEMS microrobot with a hardware neural network

This article presents the micro-electro-mechanical systems (MEMS) microrobot which demonstrates locomotion controlled by hardware neural networks (HNN). The size of the microrobot fabricated by the MEMS technology is 4 × 4 × 3.5 mm. The frame of the robot is made of silicon wafer, and it is equipped with a rotary-type actuator, a link mechanism, and six legs. The rotary-type actuator generates rotational movement by applying an electrical current to artificial muscle wires. The locomotion of the microrobot is obtained by the rotation of the rotary-type actuator. As in a living organism, the HNN realized robot control without using any software programs, A/D converters, or additional driving circuits. A central pattern generator (CPG) model was implemented as an HNN system to emulate the locomotion pattern. The MEMS microrobot emulated the locomotion method and the neural networks of an insect with the rotary-type actuator, the link mechanism, and the HNN. The microrobot performed forward and backward locomotion, and also changed direction by inputting an external trigger pulse. The locomotion speed was 0.325 mm/s and the step width was 1.3 mm.     

Extremely localized interaction in a market model

The model of self-organized criticality (SOC) is a useful tool to understand the complexity of natural systems in the form of the artificial life and the artificial market. However, SOC remains the question what guarantees the criticality even though the natural systems seem to keep itself in the critical state. In this paper, we focus on the locality of interaction in zero-intelligence plus (ZIP) model. The extremely localized interaction changes the behavior of the ZIP model from equilibrium to intermittency. Although the original ZIP model falls into unstable with some noise, extremely localized interaction model archives robust intermittency against the noise parameter. Further, the statistical property of intermittent behavior shows the power-law nature.     

Locomotion Control of MEMS Microrobot Using Pulse‐Type Hardware Neural Networks

This paper presents the locomotion control of a microelectromechanical system (MEMS) microrobot. The MEMS microrobot demonstrates locomotion control by pulse‐type hardware neural networks (P‐HNN). P‐HNN generate oscillatory patterns of electrical activity like those of living organisms. The basic component of P‐HNN is a pulse‐type hardware neuron model (P‐HNM). The P‐HNM has the same basic features as biological neurons, such as the threshold, the refractory period, and spatiotemporal summation characteristics, and allows the generation of continuous action potentials. P‐HNN has been constructed with MOSFETs and can be integrated by CMOS technology. Like living organisms, P‐HNN has realized robot control without using software programs or A/D converters. The size of the microrobot fabricated by MEMS technology was 4 × 4 × 3.5 mm. The frame of the robot was made of a silicon wafer, equipped with rotary actuators, link mechanisms, and six legs. The MEMS microrobot emulated the locomotion method and the neural networks of an insect by rotary actuators, link mechanisms, and the P‐HNN. We show that the P‐HNN can control the forward and backward locomotion of the fabricated MEMS microrobot, and that it is possible to switch its direction by inputting an external trigger pulse. The locomotion speed was 19.5 mm/min and the step size was 1.3 mm. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(3): 43–50, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.22473     

Effect of Shear Rate Distribution on Particle Aggregation in a Stirred Vessel

The modeling of particle aggregation under a simple shear flow and the extension of the model to a stirred vessel is described. The model quantitatively demonstrates the change of the number of aggregates with time for each shear rate. This number increased with higher shear rate and, conversely, the aggregate size became small when raising the shear rate. This was because aggregates were broken by the stronger shear force. The number of aggregates for different impellers was determined. The shear rate was back‐calculated from the experimentally obtained aggregate size and the model equation. This shear rate was different from that estimated from the Metzner‐Otto method, consequently, some revisions of the Metzner‐Otto equation might be necessary for its application to particle aggregation.     

A classification control strategy for energy storage system in microgrid

Storage devices are indispensable elements in a microgrid to compensate for the power imbalance between loads and the distributed generator (DG) output. Different storage strategies give diverse performances in adjustment speed and capacity. Based on the performance of different storage devices and the features of power imbalance curve in different periods, a classification control strategy is proposed in this paper. First, storage devices are given priorities according to the adjusting speed, and the power imbalance curve is divided into two periods according to the changing speed. During an emergency, all the storages are employed to compensate the rapidly increasing power imbalance; during the steady period, storage device with higher priority is employed to track the instantaneous component of power imbalance, while storage device with lower priority is used to replace the kWh output of higher priority storage. The proposed strategy is tested in a microgrid within the subdistribution network of IEEE RBTS Bus6 system using Monte Carlo methods. Simulation results indicate that the classification control strategy could endow the system with fast adjusting ability through coordination between storages. Reliability indices of the testing system are utilized to demonstrate that the classification control strategy could improve the stability of the microgrid and reliability of the distribution network. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.