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. 13 (2020), No. 4

  • Robust Control Barrier Function for Systems Affected by a Class of Mismatched Disturbances

    pp. 165-172

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    DOI:10.9746/jcmsi.13.165

    This paper proposes a robust exponential control barrier function (RECBF) for systems affected by a class of mismatched disturbances, which forces system states to remain in a given safety set expressed by constraint functions. We consider the case that given constraint functions have different relative degrees for control input and disturbances due to the property of mismatched disturbances, and we extend a concept of the nominal exponential control barrier function (ECBF) to such cases. As a main result, we show RECBF conditions to guarantee invariance of the given safety set and formulate a convex optimization based controller with the RECBF conditions. In particular, we combine a disturbance estimation using Gaussian process regression, which is one of the machine learning methods, with the controller to make use of good properties of RECBF conditions. This formulation enables us to realize robust disturbance compensation based on experimental data, and it can be easily applied to practical systems. We show the effectiveness of the proposed controller through a numerical simulation of a magnetic ball levitation system having model uncertainty.
  • A Two-Stage Optimization Scheme of Fuel Consumption and Drivability for Plug-In HEVs

    pp. 173-182

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    DOI:10.9746/jcmsi.13.173

    This paper addresses an energy consumption optimization problem with consideration of drivability improvement for series-parallel plug-in hybrid electric vehicles. Consumption of fuel and electricity are chosen as the cost function of the optimization, and the acceleration rate is involved in the constraint for improving drivability. Then, a two-stage optimization scheme is proposed, which consists of the long-term off-line optimization and the short-term on-line optimization. In the former, the entire route is dealt with as previously known, and the optimal mode switching and engine power are provided by solving the optimization problem, and in the latter, the short-term local optimization in the fashion of receding horizon is used to obtain optimality regarding the actual route situation where the vehicle-to-everything-based driver's demand prediction is involved instead of requiring previous information of the future horizon. The proposed controller was evaluated in the case of a long driving situation including the city and the motorway that required a high-power acceleration. The performance was improved in consideration of the drivability, and the fuel economy was optimized in comparison to the charge depleting and charge sustaining strategy.
  • Adaptive Gaussian Mixture Model-Based Statistical Feature Extraction for Computer-Aided Diagnosis of Micro-Calcification Clusters in Mammograms

    pp. 183-190

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    DOI:10.9746/jcmsi.13.183

    In mammography, detection and categorization of micro-calcification clusters (MCCs) using computer-aided diagnosis (CAD) systems are very important tasks because MCCs are important signs at an early stage of breast cancer. However, the conventional methods of CAD only classify MCCs into benign and malignant types, and no method has been developed for a medical requirement to classify the MCCs into more detailed categories according to the spatial distribution of MCCs. To provide a cogent second opinion, we specifically focus on analyzing MCCs' spatial distribution and propose an adaptive Gaussian mixture model-based method to extract the statistical features of the spatial distribution in this study. By mimicking the radiologists' workflow, the proposed method used the main feature of each spatial distributions to classify the MCCs and then provide a cogent second opinion to increase the confidence level of diagnosis decisions. The experiments have been performed on 100 mammographic images with MCCs from a clinical dataset. The experimental results showed that the proposed method was able to detect the MCCs and classify the spatial distribution of the MCCs effectively.
  • Development and Validation of a Measurement System for Laparoscopic Surgical Procedures

    pp. 191-200

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    DOI:10.9746/jcmsi.13.191

    This paper presents details of the development and validation of a measurement system for laparoscopic surgical procedures. An individual marker set is attached to each surgical instrument, and hence the developed system can simultaneously track multiple surgical instruments. The tracked surgical instruments can be exchanged during an operation. The movements of surgical instruments such as grasping forceps, scissors forceps, clip appliers, and needle holders are measured, and their tip positions, opening ratios, gripper rotation angles, and orientations are calculated online. Two strain gauges are attached to the gripper of the grasping forceps to measure the grasping point and force. In validation experiments, data from 46 cases of lymphadenectomy and renal parenchyma suturing using porcine cadaver organs performed by 44 subjects were acquired by measurement, and the movements of the surgical instruments used were recorded. A questionnaire survey regarding the operational feel about the surgical instruments was conducted, and the results show that this system has little impact on the operational feel.
  • Intuitive Risk Information Display via Skin for Wearable Devices

    pp. 201-207

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    DOI:10.9746/jcmsi.13.201

    This study proposes and demonstrates the feasibility of an information presentation device that presents multiple stages of information intuitively through the skin of the wrist via electrical stimulation without causing pain. Previous research into tactile displays has found that complex stimulation is required to present absolute value information in multiple stages, which is difficult to recognize intuitively. To counter this problem, we introduce intuitive electrical stimulation to give a pulse-like sensation, which is an indicator of the physical condition. We examined the waveform conditions for recognizing the difference between five stages of heatstroke risk by pulse-like stimulation. In the state of being concentrated on the stimulation, it was possible for the subject to recognize the five stages with over 80% accuracy when the ratio of the stimulation period in two adjacent stages was set to 1.6 or more. However, in the state of doing other work, the subject's recognition rate decreased to 40% at the worst recognition in all stages when changing only the stimulation period. In contrast, it was found that when the current intensity and period of the stimulation were changed, especially such that the number of period steps per current intensity step is 3 or less, the difference in stages could be recognized with accuracy of 80% or more even in the state of doing other work.
  • Bayesian LPV-FIR Identification of Wheelchair Dynamics and Its Application to Feedforward Control

    pp. 208-213

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    DOI:10.9746/jcmsi.13.208

    This paper constructs a mathematical model of wheelchair dynamics in a data-driven manner. In particular, we focus on the forward-backward movement of the wheelchair, for which we adopt a linear-parameter-varying finite-impulse-response model. To avoid overfitting behavior, we employ the Bayesian estimation method. We show by experimental results that the constructed model reproduces the observed data more precisely than linear models. We also show the identified model is effective for the feedforward input design.

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