SICE Journal of Control, Measurement, and System Integration
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ONLINE ISSN: 1884-9970
PRINT ISSN: 1882-4889

SICE Journal of Control, Measurement, and System Integration Vol. 7 (2014), No. 6

  • Preface

    pp. 313-313

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    DOI:10.9746/jcmsi.7.313

  • Mathematical Model of Glucose-Insulin Metabolism in Type 1 Diabetes Including Digestion and Absorption of Carbohydrates

    pp. 314-320

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    DOI:10.9746/jcmsi.7.314

    The authors propose a mathematical model of glucose-insulin metabolism in type 1 diabetes based on Bergman and Shimoda insulin models, which are adjusted to represent diabetic state and improve the accuracy of subcutaneous insulin absorption, respectively. The authors also propose a model of digestion and absorption from carbohydrates based on the glycemic index (GI) of foods and carbohydrate bioavailability concepts that provide a glucose-equivalent representation of the impact of carbohydrates on blood glucose levels. Comparison with clinical data demonstrates that the proposed model is able to represent postprandial blood glucose excursion for carbohydrates with varying GI values.
  • System Identification of Mechanomyogram at Various Levels of Motor Unit Recruitment

    pp. 321-326

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    DOI:10.9746/jcmsi.7.321

    The mechanomyogram from a single motor unit and the induced mechanomyogram at various levels of recruitment were measured with an acceleration sensor. The transfer functions between motor unit action potential (or electrical stimulation) and the mechanomyogram were identified using the singular value decomposition method. The purpose of this study is to clarify how the model order of the transfer function depends on the recruitment level. The second- to tenth-order transfer functions were calculated, and the difference between the observed and the estimated mechanomyograms using the transfer function, the fitness, was calculated. The relationship between the model order and the fitness was tested using the Holm-Bonferroni multiple comparison. At low levels (single motor unit, 20, and 40%) of recruitment, there were significant differences between the fourth- and higher-order models, but there were no significant differences between the fifth- and higher-order models. In contrast, at high levels (60, 80, and 100%) of recruitment, the fourth-order model did not show significant differences between the fifth- or higher-order models. As a result, the fifth- and fourth-order models were appropriate at low and high recruitment levels, respectively. The differences in the order might be caused by interactions between active and resting motor units.
  • Near-Infrared Spectroscopy Measurement for Brain Activity Analysis during Ergometer Pedal Exercise

    pp. 327-331

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    DOI:10.9746/jcmsi.7.327

    The goal of this research is to develop a rehabilitation system based on a brain-machine interface (BMI) for paraplegic patients. This requires the ability to detect a patient's desire on the basis of his or her brain activity. In the work reported here, the authors used near-infrared spectroscopy (NIRS) to measure the brain activity of healthy subjects while they exercised on a bicycle ergometer. Analysis results showed that the oxy-Hb level increased at the start of the exercise. This variation in the oxy-Hb level occurred a few seconds after the start of exercise. On the basis of the analysis results, the authors considered a pedaling exercise state discrimination that uses the oxy-Hb level and its time derivative. The discrimination results for three healthy subjects showed over 72% accuracy. For a paraplegic patient's pedal exercise imagery, this discrimination scheme still had 74% accuracy.
  • Simultaneous Measurement of Displacement-MMG/EMG during Exercise

    pp. 332-336

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    DOI:10.9746/jcmsi.7.332

    A surface electromyogram (sEMG) is a time-related and spatial aggregate of the action potentials of a muscle's motor units. A mechano-myogram (MMG) directly reflects the mechanical contraction function of a muscle. A displacement-MMG is useful to examine the characteristics of muscle contraction. To evaluate muscle contraction, it is necessary to measure both EMG and MMG signals (EMG: input to muscles that will contract, MMG: resulting output from contraction). The authors developed a wireless MMG/EMG hybrid transducer (45L × 16W × 12mmH, 2.5g) composed of a small photo-reflector, two EMG electrodes, and a wireless transmission module. It can measure both EMG and MMG signals simultaneously. The authors applied the transducer to the measurement of displacement-MMG/EMG signals during subjects' squatting-jumping, ergometer pedaling and running on a treadmill. The authors also examined the relationship between the MMG and EMG signals recorded.
  • Entrainment Analysis in Goodwin-Type Nonlinear Oscillator Networks Driven by External Periodic Signals

    pp. 337-346

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    DOI:10.9746/jcmsi.7.337

    In this paper, we present a systematic approach based on harmonic balance method to study the entrained oscillations in a class of Goodwin-type oscillator networks forced by external periodic signals consisting of high order harmonics. First, a necessary condition and a conjecture for entrainment of network oscillations are presented. Next, the authors reveal an estimation for the profile of entrained oscillations in one situation and the monotone dependence of the amplitude and phase shift of entrained oscillations to the external input in other contexts. The theoretical results are then illustrated through some examples including a practical model for circadian rhythm in Neurospora crassa.
  • Collision-Free Guidance Control of Small Unmanned Helicopter Using Nonlinear Model Predictive Control

    pp. 347-355

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    DOI:10.9746/jcmsi.7.347

    In this study, our aim is to realize collision-free guidance control for a small unmanned helicopter. The simultaneous flight of multiple small unmanned helicopters has recently attracted considerable attention for practical operation because of the high efficiency and fault tolerance capability. Collision avoidance should be considered in the guidance system of small helicopters to realize simultaneous flight. The authors adopted nonlinear model predictive control (NMPC) to design a collision-free guidance control system for small unmanned helicopters; collision avoidance was regarded as a state constraint. A hierarchical control structure consisting of an attitude control system and guidance control system was adopted to simplify the overall control system. The authors propose a simple nonlinear translational model of the helicopter to reduce the computational cost of NMPC. The effectiveness of the proposed collision-free guidance control system was verified through both numerical simulation and a flight experiment.
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  • A Pragmatic Approach to Modeling Object Grasp Motion Using Operation and Pressure Signals for Demolition Machines

    pp. 356-363

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    DOI:10.9746/jcmsi.7.356

    In this paper, an object grasp motion, which is a requisite condition to make a demolition machine grasp an object, is pragmatically modeled, considering accurate and robust identification. Grasping an object is a highly difficult task that requires safe and precise operations, particularly in disaster response work. Identifying a grasp or non-grasp state is essential for providing operational support. These types of outdoor machines lack visual and tactile sensors, so pragmatically available lever operation and cylinder pressure sensors are adopted as parameters for modeling. The grasp motion is simply defined by using sequential transitions of the on-off state of the operation signal and cylinder pressure data for the grapple and the manipulator. The results of experiments conducted to transport objects using an instrumented hydraulic arm indicated that the modeled grasp motion model effectively identifies a grasp or non-grasp state with high accuracy, independently of operators and work environments.
  • Stabilization of Suspension Vehicle Near Rollover by Nonlinear Model Predictive Control

    pp. 364-373

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    DOI:10.9746/jcmsi.7.364

    A suspension vehicle near rollover is controlled by nonlinear model predictive control method (NMPC), in which the continuation/generalized minimal residual (C/GMRES) is used to solve an optimal control problem in real time. The suspension vehicle near rollover can be represented by a double inverted pendulum with suspension. This kind of double inverted pendulum consists of two pendulums connected together by a nonlinear spring, which represents the axle and the body of the suspension vehicle. The terminal cost is given by a solution to the algebraic Riccati equation to make the tuning process in performance index easier. The input force to make the vehicle tip up is determined based on the surface friction coefficient and the location of the vehicle's center of gravity. The results obtained from simulation indicated that NMPC with C/GMRES could swing up and stabilize the system successfully in real time.

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