Transactions of the Institute of Systems, Control and Information Engineers
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ONLINE ISSN: 2185-811X
PRINT ISSN: 1342-5668

Transactions of the Institute of Systems, Control and Information Engineers Vol. 30 (2017), No. 8

  • Construction of OTEC Potential Model Based on Cycle Analysis

    pp. 297-304

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    DOI:10.5687/iscie.30.297

    In ocean thermal energy conversion (OTEC) plant, electricity is generated by heat energy came from temperature difference between warm seawater at surface and cold seawater in depth. OTEC power potential has been calculated to introduce OTEC plant by considering the seawater condition. In this paper, an OTEC potential model is constructed by taking into account the cycle analysis. First, state quantities and evaluation indexes of an OTEC plant using Rankine cycle are calculated. Secondly, parameters about power potential, purchase cost and environmental burden are calculated. Finally, simulation results are shown to verify the behavior of the constructed model.
  • SVM-based Multi-point Prediction System of Solar Irradiance using DTW-based Cluster Analysis

    pp. 305-313

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    DOI:10.5687/iscie.30.305

    Unexpected short-term fluctuation of solar irradiance may negatively affect an electric power system; hence, predicting the solar irradiance is necessary. Considering that large quantities of solar power will be introduced across wide areas in the future, this paper addresses multi-point predictions of solar irradiance. Support vector machines (SVMs) perform well for predicting solar irradiance,but involve relatively high computational complexity. In addition, SVMs have to be repeatedly computed at multiple points because prediction models need to be updated regularly to adapt to the season. Here, we introduce a multi-point prediction system that considerably reduces the amount of calculation. Instead of constructing prediction models at all grid points, this system establishes clusters based on similarities of time series data by executing the dynamic time warping algorithm, and then constructs a small number of models representing each cluster. Further, it automatically tunes the number of clusters by inspecting prediction accuracy. Simulation results reveal that the system saves a considerable amount of calculation while maintaining high prediction accuracy.
  • Disturbance Road Driving Control for Power-Assisted Wheelchair Based on User Evaluation Map

    pp. 314-322

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    DOI:10.5687/iscie.30.314

    The “power-assisted wheelchair” that assists the driving force by electric motors is expected to be widely used as a mobility support system for elderly people and disabled people; however, there are lots of large disturbance roads such as uphill roads and rough roads and operators need to push handrims with larger power load to obtain enough driving distance and velocity. Therefore this paper proposes a driving control scheme of power-assisted wheelchairs for the comfortable and safety driving on large disturbance roads. This study constructs the individual user evaluation maps with optimal driving parameters in advance in order to realize the comfortable and safety driving which depends on users and disturbance roads. The proposed control system estimates the driving disturbance level and determines some driving parameters based on user evaluation maps. The optimal assistance ratio and target driving distance are designed according to the disturbance level and user preference. Some experiment results are provided to show the effectiveness of the proposed driving control system.
  • An Identification Method with Estimation of Variances and the Covariance of Input and Output Noises for Single-Input Single-Output Linear Systems

    pp. 323-329

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    DOI:10.5687/iscie.30.323

    A new algorithm is proposed to estimate parameters of SISO (Single-Input Single-Output) system. The algorithm is an expansion of the previously proposed algorithms by the author with iterative estimation of the variances of noises. The previously proposed algorithms are based on the assumption that input and output noises have no correlation. Whereas, the method proposed in this paper is available even if input and output noises have correlation. This algorithm uses an iterative calculation and it consists of two parts. One part is the estimation of the system parameters by use of the variance and covariance matrix of input and output noises. The estimation of the system parameters is one of the least squares identification algorithms using eigenvector. The other part is the estimation of the variances and covariances of input and output noises using the system parameters. The variances and covariance of noises are estimated by solving linear simultaneous equations derived from the system parameters of transfer functions. The simulation results show the effectiveness of the proposed method.
  • A Fault-Tolerant Adaptive Control Design and Fault Detection with Input Redundancy for a 2-input Redundant Plant

    pp. 330-337

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    DOI:10.5687/iscie.30.330

    In this paper, we propose an active fault detection scheme with input redundancy of the plant. The proposed active fault detection scheme aims at quickly detecting of the occurrence of actuator sticking under steady state. In addition, a new fault tolerant control (FTC) design is developed to implement the active fault detection scheme for input redundant 2-input 1-output plant. Finally, the effectiveness of the proposed FTC and the applicability of the proposed active fault detection scheme are verified through several experiments.

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