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SICE Journal of Control, Measurement, and System Integration Vol. 13 (2020), No. 5

ISIJ International
ONLINE ISSN: 1884-9970
PRINT ISSN: 1882-4889
Publisher: The Society of Instrument and Control Engineers

Backnumber

  1. Vol. 13 (2020)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  2. Vol. 12 (2019)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  3. Vol. 11 (2018)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  4. Vol. 10 (2017)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  5. Vol. 9 (2016)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  6. Vol. 8 (2015)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  7. Vol. 7 (2014)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  8. Vol. 6 (2013)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  9. Vol. 5 (2012)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  10. Vol. 4 (2011)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  11. Vol. 3 (2010)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  12. Vol. 2 (2009)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

  13. Vol. 1 (2008)

    1. No.6
    2. No.5
    3. No.4
    4. No.3
    5. No.2
    6. No.1

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22 Dec. (Last 30 Days)

SICE Journal of Control, Measurement, and System Integration Vol. 13 (2020), No. 5

Load Frequency Control and Real-Time Pricing with Stochastic Model Predictive Control

Taro YANAGIYA, Yusuke OKAJIMA, Tomoaki HASHIMOTO, Toshiyuki OHTSUKA

pp. 215-224

DOI:

10.9746/jcmsi.13.215

Abstract

We developed a load frequency control system with stochastic model predictive control (SMPC) for power systems where the market penetration of wind power generation is high. The controller adjusts the electricity price for heat pump water heaters while at the same time controlling thermal power plants and batteries in order to maintain the frequency in the designated range. We propose an approach for solving SMPC problems on Hammerstein models including affine disturbance feedback parametrization. Simulation results show that SMPC with affine disturbance feedback parametrization outperforms both SMPC without parametrization and deterministic model predictive control in terms of the stage-cost and constraint violation.

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Load Frequency Control and Real-Time Pricing with Stochastic Model Predictive Control

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Relative Position Estimation for Formation Control with the Fusion of Predicted Future Information and Measurement Data

Tsuyoshi OGAWA, Kazunori SAKURAMA, Shintaro NAKATANI, Shin-ichiro NISHIDA

pp. 225-232

DOI:

10.9746/jcmsi.13.225

Abstract

This paper addresses a relative position estimation problem for formation control of multiple robots. In the authors' previous paper, a relative position estimation method has been proposed, which fuses information from distance sensors and wireless communication. In this method, it is assumed that the robots communicate with others by wireless devices at every control sampling time. Therefore, depending on the performance of the wireless devices, the control sampling time should be set to a large value, which can degrade control performance. In this paper, we propose a new relative position estimation method, which is effective even if the communication sampling time is longer than the control sampling time. The idea in this method is to use predicted information on the time-series of the control input from detected robots. We develop a method to generate the time-series of the predicted control input for successful estimation. Finally, we verify the effectiveness of the proposed method by simulations and an experiment.

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Relative Position Estimation for Formation Control with the Fusion of Predicted Future Information and Measurement Data

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Stability Optimization of Positive Semi-Markov Jump Linear Systems via Convex Optimization

Chengyan ZHAO, Masaki OGURA, Kenji SUGIMOTO

pp. 233-239

DOI:

10.9746/jcmsi.13.233

Abstract

In this paper, we study the problem of optimizing the stability of positive semi-Markov jump linear systems. We specifically consider the problems of tuning the coefficients of the system matrices for maximizing the exponential decay rate of the system under a budget-constraint and minimizing the parameter tuning cost under the decay rate constraint. By using a result from the matrix theory on the log-log convexity of the spectral radius of nonnegative matrices, we show that the stability optimization problems are reduced to convex optimization problems under certain regularity conditions on the system matrices and the cost function. We illustrate the validity and effectiveness of the proposed results by using an example from the population biology.

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Stability Optimization of Positive Semi-Markov Jump Linear Systems via Convex Optimization

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A Performance Evaluation of Periodic Signal Analysis by ARS Compared with Frequency Analysis by FFT

Ryota TAKAO, Yukihiro KAMIYA

pp. 240-248

DOI:

10.9746/jcmsi.13.240

Abstract

Accumulation for real-time serial-to-parallel converter (ARS) has been proposed as a computationally-efficient method for signal analysis. Since it consists of additions and a few divisions only, it was shown that the computational load is drastically reduced compared with the fast Fourier transform (FFT). In this paper, we clarify that ARS achieves a higher resolution in low-frequency bands comparing with FFT. In addition, selection criteria between ARS and FFT are clarified theoretically in terms of the resolution. Through the performance analysis of ARS in low-frequency bands, it is expected that ARS is a powerful tool for signal analysis in the Internet of Things realizing the edge computing.

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A Performance Evaluation of Periodic Signal Analysis by ARS Compared with Frequency Analysis by FFT

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Synthesis of Memory Gain-Scheduled Controllers for Discrete-Time LPV Systems

Izumi MASUBUCHI, Yuta YABUKI

pp. 249-255

DOI:

10.9746/jcmsi.13.249

Abstract

This paper considers synthesis of discrete-time gain-scheduled controllers for linear parameter varying systems based on linear matrix inequalities (LMIs). Unlike most of the previous results, gain-scheduled controllers that depend on memory of the scheduling parameters are investigated in this paper. Through the method of change-of-variables, parameter-dependent LMIs are obtained for synthesis of gain-scheduled controllers from extended LMIs for H∞ and H2 performances. Numerical examples are provided to illustrate the proposed synthesis methods.

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Synthesis of Memory Gain-Scheduled Controllers for Discrete-Time LPV Systems

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