IEEE Transactions on Automatic Control

Issue 6 • December 1974

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Displaying Results 1 - 25 of 46
  • [Front cover and table of contents]

    Publication Year: 1974, Page(s): 0
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  • Introduction

    Publication Year: 1974, Page(s):638 - 640
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  • Some recent advances in time series modeling

    Publication Year: 1974, Page(s):723 - 730
    Cited by:  Papers (214)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (801 KB)

    The aim of this paper is to describe some of the important concepts and techniques which seem to help provide a solution of the stationary time series problem (prediction and model identification). Section I reviews models. Section II reviews prediction theory and develops criteria of closeness of a "fitted" model to a "true" model. The central role of the infinite autoregressive transfer function... View full abstract»

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  • A class of bootstrap estimators and their relationship to the generalized two stage least squares estimators

    Publication Year: 1974, Page(s):831 - 835
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (428 KB)

    This paper deals with the identification of a process modeled by a stable, linear difference equation of known order. Its output is subject to additive observation noise that is identically and independently distributed with zero mean and a constant variance. On-line estimators in which the process parameters as well as the process outputs are estimated simultaneously in real time are considered. ... View full abstract»

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  • Identification and autoregressive spectrum estimation

    Publication Year: 1974, Page(s):894 - 898
    Cited by:  Papers (59)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (521 KB)

    In recent years there has been increasing interest in autoregressive spectrum estimation. This procedure fits a finite autoregression to the time series data, and calculates the spectrum from the estimated autoregression coefficients and the one step prediction error variance. For multivariate time series, the estimated autoregressive matrices and one step prediction covariance matrix produce esti... View full abstract»

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  • [Back cover]

    Publication Year: 1974, Page(s): 0
    Cited by:  Papers (3)
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  • Parameter estimation for power systems in the steady state

    Publication Year: 1974, Page(s):882 - 886
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (592 KB)

    This paper addresses itself to the variety of model inaccuracy problems arising in the implementation of on-line state estimation for power system bulk transmission networks. Two classes of models are investigated for which parameter estimation algorithms are derived and simulated. The first class consist of network and measurement system parameters of the system being monitored. The second class ... View full abstract»

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  • Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model

    Publication Year: 1974, Page(s):769 - 773
    Cited by:  Papers (128)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (456 KB)

    Estimation of the parameters in a mixed autoregressive moving average process leads to a nonlinear optimization problem. The negative logarithm of the likelihood function, suitably normalized, converges to a deterministic function as the sample length increases. The local and global extrema of this function are investigated. Conditions for the existence of a unique global and local minimum are giv... View full abstract»

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  • A self-tuning predictor

    Publication Year: 1974, Page(s):848 - 851
    Cited by:  Papers (60)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (416 KB)

    An adaptive predictor for discrete time stochastic processes with constant but unknown parameters is described. The predictor which in real time tunes its parameters using the method of least squares is called a self-tuning predictor. The predictor has attractive asymptotic properties. If the parameter estimation converges and if the predictor contains parameters enough, then it will converge to t... View full abstract»

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  • State-space models for infinite-dimensional systems

    Publication Year: 1974, Page(s):693 - 700
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (944 KB)

    Distributed effects are present in almost all physical systems. In some cases these can be safely ignored but there are many interesting problems where these effects must be taken into account. Most infinite dimensional systems which are important in control theory are specifiable in terms of a finite number of parameters and hence are, in principle, amenable to identification. The state-space the... View full abstract»

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  • Stochastic approximation methods for identification and control--A survey

    Publication Year: 1974, Page(s):798 - 809
    Cited by:  Papers (61)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (968 KB)

    Stochastic search techniques have been the essential part for most identification and self-organizing or learning control algorithms for stochastic systems. Stochastic approximation search algorithms have been very popular among the researchers in these areas because of their simplicity of implementation, convergence properties, as well as intuitive appeal to the investigator. This paper presents ... View full abstract»

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  • Canonical forms for the identification of multivariable linear systems

    Publication Year: 1974, Page(s):646 - 656
    Cited by:  Papers (70)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1024 KB)

    The advantage of using a unique parameterization in a numerical procedure for the identification of a system from operating records has been well established. In this paper several sets of canonical forms are described for state space models of deterministic multivariable linear systems; the members of these sets having therefore the required uniqueness property within the equivalence classes of m... View full abstract»

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  • Coupled design of test signals, sampling intervals, and filters for system identification

    Publication Year: 1974, Page(s):748 - 752
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (432 KB)

    This paper discusses the problem of optimal design of experimental conditions for linear system identification. It is demonstrated that, in general, to achieve maximal return from an experiment, coupled design of all the experimental conditions, namely the test signal, sampling intervals and filters, should be carried out simultaneously. For the case of uniform sampling it is shown that joint desi... View full abstract»

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  • Time series analysis

    Publication Year: 1974, Page(s):706 - 715
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1168 KB)

    This paper begins with a discussion of the properties of the noise occurring in the structures considered. This noise is taken to be generated by a stationary, ergodic, purely nondeterministic process. In case the observed vector sequence is generated by an autoregressive-moving average process then (a little more than) the additional requirement that the best predictor be the best linear predicto... View full abstract»

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  • Stochastic theory of minimal realization

    Publication Year: 1974, Page(s):667 - 674
    Cited by:  Papers (201)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (904 KB)

    In this paper it is shown that a natural representation of a state space is given by the predictor space, the linear space spanned by the predictors when the system is driven by a Gaussian white noise input with unit covariance matrix. A minimal realization corresponds to a selection of a basis of this predictor space. Based on this interpretation, a unifying view of hitherto proposed algorithmica... View full abstract»

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  • Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations

    Publication Year: 1974, Page(s):774 - 783
    Cited by:  Papers (157)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (960 KB)

    This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discus... View full abstract»

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  • Least squares estimates of structural system parameters using covariance function data

    Publication Year: 1974, Page(s):898 - 903
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (656 KB)

    A statistically efficient and computationally economical two-stage least squares procedure for the estimation of the natural frequencies and damping parameters of structural systems under stationary random vibration conditions is considered. The structural system is represented by the system of ordinary differential equations that is characteristic of lumped mass-spring-damper systems with a rando... View full abstract»

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  • On the spectral factorization of nonstationary vector random processes

    Publication Year: 1974, Page(s):674 - 679
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (648 KB)

    Conditions which depend on the covariance of a vector random process, sufficient to ensure the process can be generated by a linear, invertible system of finite order driven by white noise are derived, and equations which determine the parameters of the system are found. Some structural properties of lumped covariances are given; these stress the close relation between the structure of linear syst... View full abstract»

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  • III-posed and well-posed problems in systems identification

    Publication Year: 1974, Page(s):738 - 747
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (944 KB)

    Impulse response identification almost always leads to an ill-posed mathematical problem. This fact is the basis for the well-known numerical difficulties of identification by means of the impulse response. The theory of regularizable ill-posed problems furnishes a unifying point of view for several specific methods of impulse response identification. In this paper we introduce a class of input/ou... View full abstract»

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  • A new look at the statistical model identification

    Publication Year: 1974, Page(s):716 - 723
    Cited by:  Papers (18090)  |  Patents (45)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (896 KB)

    The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) ... View full abstract»

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  • Applications of principal component analysis and factor analysis in the identification of multivariable systems

    Publication Year: 1974, Page(s):730 - 734
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (552 KB)

    The identification of a multivariable stochastic system, usually, involves the estimation of a transfer function matrix, which is a general function of frequency. This estimation involves inversion of a large Hermitian matrix, which sometimes may become unwieldly. In this paper we describe how "principal component analysis" in the frequency domain may be used to replace the input/output variables ... View full abstract»

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  • Parameter estimation in the canine cardiovascular system

    Publication Year: 1974, Page(s):927 - 931
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (624 KB)

    A new method of parameter estimation has been developed to estimate a newly chosen group of eight parameters of the canine arterial system. These parameters, which are physically meaningful, include arterial radii, Young's modulus for the aortic wall, aortic length, and peripheral resistances. The method is model-based, and depends upon minimization of a criterion which combines weighted integrals... View full abstract»

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  • Macroeconomic modeling for control

    Publication Year: 1974, Page(s):862 - 873
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1152 KB)

    This paper describes briefly the modeling of the United Kingdom economy in the least complex structural form allowable for the application of modern control techniques. The method employed is a blend of the "black box" approach where no knowledge of the inner mechanism is assumed and the classical approach of econometrics where economic theory is used to determine structure. The technique is illus... View full abstract»

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  • Stochastic modeling of river flows

    Publication Year: 1974, Page(s):874 - 881
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (848 KB)

    A family of linear stochastic difference equation models is proposed for monthly river flows, the variance of the disturbance in the model varying sinusoidally with time. The unknown parameters in the model are estimated by using the given data and an algorithm is given for the choice of the appropriate number and type of autoregressive terms, sinusoidal trend terms, etc., in the model. The method... View full abstract»

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  • Linear time dependent systems

    Publication Year: 1974, Page(s):735 - 737
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (312 KB)

    In studies of linear open-loop systems, the assumption of time invariance is often tacitly made. In this paper we show how a time dependent system can arise quite naturally. The estimation of time dependent transfer function, on the basis of a single realization, when the input/output processes are nonstationary is considered. We also consider the problem of testing a given open-loop system for ti... View full abstract»

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In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering.  Two types of contributions are regularly considered

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Meet Our Editors

Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame