Transactions of the Institute of Systems, Control and Information Engineers
New Arrival Alert : OFF

You can use this feature after you logged into the site.
Please click the button below.

Log in / Sign up
ONLINE ISSN: 2185-811X
PRINT ISSN: 1342-5668

Transactions of the Institute of Systems, Control and Information Engineers Vol. 12 (1999), No. 4

  • An Approximate Maximum Likelihood Estimation of a Class of Nonlinear Systems Using Neural Networks and Noise Models

    pp. 203-211

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.203

    This paper proposes an identification method for a class of nonlinear systems using a neural network and a noise model. A three-layer neural network is used as a plant model of the nonlinear system, and the noise model is applied as a whitening filter. Since noise can not be observed directly, an identification method is proposed in which the neural network and the noise model are calculated with the bootstrap method. We are able to obtain the approximate maximum estimated value of the nonlinear system, where the estimated value is determined based on Akaike's information criterion.
    Simulation results are shown to show the effectiveness of the proposed method. The validity of the obtained model is investigated by evaluating the covariance of an estimate error, means, and residual tests. Finally, the simulation result of the undisturbed output and the output of the obtained model are compared and it is shown that a neural network following the undisturbed output and a whitening filter are obtained.
  • Associative Classification Using the Extended Associatron

    pp. 212-219

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.212

    This paper deals with classification problem, such as diagnosis, in which classes are defined by categorical forms. Supposing there are some sample data, and each datum has n kinds of characteristic values. The problem to classify these samples into given m classes based on their characteristic values has been discussed for a long period of time. However, classic methods including the discriminant analysis are difficult to be applied to actual problems, because the assumption of multivariate normal distribution and equality of variance-covariance matrices are needed.
    In this paper we propose a classification method using the associatron as an associative memory machine. We extend the associatron so as to have stable three leveled outputs following in the steps of a method given by Kanagawa et al. Examples of diagnosis of liver disease and the problem of iris classification are demonstrated.
  • Stabilization of Periodic Discrete Systemsby Output Sample Hold Control

    pp. 220-224

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.220

    In linear ω-periodic discrete-time systems, eigenvalues of the state transition matrix over the time interval nω dominate stability, where n is the dimension of the state vector. The periodic discrete-time system is called to be sample observable when the state can be determined from observation of output at only one time within one period. Under the assumption that eigenvalues of the monodromy matrix in an open-loop system are distinct, it is shown that the closed-loop system can be stabilized by applying the sampled output nω-periodic hold control if and only if the open-loop system is stabilizable and sample detectable at some time t0.
  • The Back Propagation Method Using the Least Mean-Square Method for the Output Recurrent Neural Network

    pp. 225-233

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.225

    The back propagation method on the basis of the gradient method is often utilized as a learning rule of a neural network. This paper proposes a back propagation method using the least mean-square method for the output recurrent neural network. The approach consists of the decision of the input vector and the parameter estimation of each layer. The input vector of the output layer is corrected to decrease the output error corresponding to learning rate and the learning value of the other layer. The parameter is calculated using the least-square method from the obtained input and output of each layer.
    The identification result for the linear oscillation system shows the effectiveness of the proposed algorithm which is not based on the gradient method. It is shown that better estimate is obtained by the proposed algorithm compared with the classical back propagation method.
  • A Frequency-Domain Validation Test for Uncertainty Models Having White Noise and Unmodeled Dynamics

    pp. 234-239

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.234

    In this paper, we propose a new frequency-domain validation test for uncertainty models having white noises and norm-bounded unmodeled dynamics. In this method, a statistical whiteness test is integrated into the deterministic model validation methodology and we consider the whiteness test based on the averaged periodogram of data segments in order to reduce the validation problem into a convex problem with less computation burden. One of the distinguished features of our method is that the quality of the validation test can be improved by increasing the data segments because of the whiteness test. Also, one of the merits of our frequency-domain validation test is that we need a priori information in time-domain only. A numerical example is given to illustrate the effectiveness of the proposed method.
  • Adaptation to a Changing Environment by Means of the Thermodynamical Genetic Algorithm

    pp. 240-249

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.240

    In the genetic algorithms (GAs), maintenance of the diversity of the population is an important issue to enhance their optimization and adaptation ability. The authors have proposed the thermodynamical genetic algorithm (TDGA), which can maintain the diversity explicitly and systematically by evaluating the diversity of the population as entropy and by selecting offspring so as to minimize the free energy. In applications of the GA to problems of adaptation to changing environments, maintenance of the diversity is an essential requirement because it is a key factor of the GA in yielding novel search points continuously for adaptation. This paper discusses adaptation to changing environment by means of TDGA. The authors propose a control method of the temperature, an adjustable parameter in the TDGA. That is, the temperature is controlled by a feedback technique so as to regulate the level of the entropy of the population. The adaptation ability of the proposed method is confirmed by computer simulation taking time-varying knapsack problems as examples.
  • Iterative Learning Control Based on the Gradient Method for Linear Discrete-Time Systems

    pp. 250-259

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.250

    In this paper, we discuss convergence of iterative learning control based on the gradient method for linear discrete-time systems. First, it is shown that residuals generated by the algorithm converge exponentially and therefore, observation errors or disturbance does not cause divergence. Second, the convergence conditions are expressed as strictly positive realness of the ratio of transfer functions. Conditions for the strictly positive realness is presented when there exists uncertainty of parameters in the transfer function and it is known that they are in given intervals. We also propose a simple sufficient condition for the strictly positive realness, which is based on a special structure of the problem. Finally, we illustrate design procedure based on the results given in this paper. Applications of the results to sampled-data systems are also discussed.
  • Adaptive Gains for Discrete-Time SAC Based on AOT Theory

    pp. 260-262

    Bookmark

    You can use this feature after you logged into the site.
    Please click the button below.

    Log in / Sign Up

    DOI:10.5687/iscie.12.260

Article Access Ranking

18 Jan. (Last 30 Days)

  1. A Review of the Chemistry, Structure and Formation Conditions of Silico-Ferrite of Calcium and Aluminum (‘SFCA’) Phases ISIJ International Vol.58(2018), No.12
  2. Improving Blast Furnace Raceway Blockage Detection. Part 1: Classification of Blockage Events and Processing Framework ISIJ International Advance Publication
  3. Phase Transformation Behavior of Oxide Scale on Plain Carbon Steel Containing 0.4 wt.% Cr during Continuous Cooling ISIJ International Vol.58(2018), No.12
  4. Hydrogen Embrittlement Susceptibility Evaluation of Tempered Martensitic Steels Showing Different Fracture Surface Morphologies Tetsu-to-Hagané Vol.105(2019), No.1
  5. Gasification and Migration of Phosphorus from High-phosphorus Iron Ore during Carbothermal Reduction ISIJ International Vol.58(2018), No.12
  6. Effect of Coke Size on Reducing Agent Ratio (RAR) in Blast Furnace ISIJ International Vol.58(2018), No.12
  7. Improvement of Sinter Productivity by Control of Magnetite Ore Segregation in Sintering Bed ISIJ International Vol.58(2018), No.12
  8. Heat Transfer Characteristic of Slit Nozzle Impingement on High-temperature Plate Surface ISIJ International Advance Publication
  9. High Temperature Thermal Diffusivity Measurement for FeO Scale by Electrical-Optical Hybrid Pulse-Heating Method ISIJ International Vol.58(2018), No.12
  10. Effect of TiO2 and MnO on Viscosity of Blast Furnace Slag and Thermodynamic Analysis ISIJ International Vol.58(2018), No.12

Search Phrase Ranking

18 Jan. (Last 30 Days)

  1. blast furnace
  2. blast furnace productivity
  3. blast furnace permeability
  4. 鉄と鋼
  5. laser welder
  6. titanium
  7. activity feo
  8. argon steel
  9. continous annealing
  10. eaf operation