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IEEE Transactions on Automatic Control

Issue 6 • Date 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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    Freely Available from IEEE
  • Introduction

    Publication Year: 1974, Page(s):638 - 640
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    Freely Available from IEEE
  • [Back cover]

    Publication Year: 1974, Page(s): 0
    Cited by:  Papers (3)
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    Freely Available from IEEE
  • Identification and autoregressive spectrum estimation

    Publication Year: 1974, Page(s):894 - 898
    Cited by:  Papers (58)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 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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  • Parameter estimation in the canine cardiovascular system

    Publication Year: 1974, Page(s):927 - 931
    Cited by:  Papers (7)
    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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  • Identification of linear, multivariable systems operating under linear feedback control

    Publication Year: 1974, Page(s):836 - 840
    Cited by:  Papers (78)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (520 KB)

    The possibility of estimating process parameters using input-output data collected when the system operates in closed loop is discussed in this paper. Concepts that are useful for a systematic treatment of the problem are introduced. The results refer to the case where the regulator is a linear feedback law or alternates between several such laws. It is shown that a straightforwardly applied ident... View full abstract»

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  • Stable adaptive schemes for state estimation and identification of linear systems

    Publication Year: 1974, Page(s):841 - 847
    Cited by:  Papers (26)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (712 KB)

    The main contribution of this paper is the introduction of a new canonical form for an adaptive observer for a linear multivariable system. The adaptive observer simultaneously estimates the state and the parameters of the unknown plant and is shown to be globally asymptotically stable. The extension of the results to discrete systems and the application of the adaptive observer in the control of ... View full abstract»

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  • Optimal input signals for parameter estimation in dynamic systems--Survey and new results

    Publication Year: 1974, Page(s):753 - 768
    Cited by:  Papers (131)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1544 KB)

    This paper surveys the field of optimal input design for parameter estimation as it has developed over the last two decades. Many of the developments covered are only recent and have not appeared in the open literature elsewhere. After a brief introduction, the paper discusses the historical background of the subject both in the engineering and in the statistical literature. The concepts of optima... 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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  • On the structure of a class of nonlinear systems

    Publication Year: 1974, Page(s):701 - 706
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (584 KB)

    Nonlinear systems composed of linear dynamic sub-systems in cascade with static power nonlinearities are considered. A structure theory is developed based on the representation of input/output behavior by rational functions in several variables. An algorithm is given which solves the minimal complete realization problem for two forms of the representation. Examples are worked in detail to illustra... View full abstract»

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  • Code for a general purpose system identifier and evaluator (GPSIE)

    Publication Year: 1974, Page(s):852 - 854
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (352 KB)

    The modeling process may be viewed as a three-step iteration: 1) hypothesize a structure, 2) estimate (identify) unknown parameters, and 3) test for consistency between the model and available data. This paper describes a new, publicly-available computer program which performs the second and third tasks. The program, called General Purpose System Identifier and Evaluator (GPSIE), can handle nonlin... 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 (26)
    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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  • Identification of human driver models in car following

    Publication Year: 1974, Page(s):911 - 915
    Cited by:  Papers (35)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (456 KB)

    This paper presents the development of two new mathematical models of driver behavior in single-lane car following situations. Optimum parameter values in each of these models were obtained using standard parameter identification algorithms. The basic approach to model development was to derive the model structure using optimal control theory. The problem was formulated as a model-tracking problem... View full abstract»

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  • Spectral factorization of a finite-dimensional nonstationary matrix covariance

    Publication Year: 1974, Page(s):680 - 692
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1384 KB)

    For a given nonstationary matrix covariance with a finite-dimensionality property that is the time-varying generalization of the rational power spectrum matrix property, we show how to find a linear finite-dimensional system driven by white noise with output covariance equal to the prescribed covariance. View full abstract»

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  • Gradient estimation algorithms for equation error formulations

    Publication Year: 1974, Page(s):820 - 824
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (464 KB)

    This paper presents the theory for and illustrates the application of gradient parameter estimation algorithms which have been developed for equation error formulations of parameter identification problems. These algorithms are computationally simple; hence, they are ideal candidates for on-line applications. They are limited, however, by availability of first- and second-order statistics of noise... View full abstract»

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  • Stochastic modeling of river flows

    Publication Year: 1974, Page(s):874 - 881
    Cited by:  Papers (8)
    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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  • A new look at the statistical model identification

    Publication Year: 1974, Page(s):716 - 723
    Cited by:  Papers (14786)  |  Patents (42)
    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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  • State-space models for infinite-dimensional systems

    Publication Year: 1974, Page(s):693 - 700
    Cited by:  Papers (6)
    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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  • Error and sensitivity analysis of stochastic approximation algorithms for linear system identification

    Publication Year: 1974, Page(s):810 - 815
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (576 KB)

    Propagation of errors in identifying constant coefficient parameters of a discrete time linear system, using stochastic approximation algorithms, is investigated. Error and sensitivity analysis algorithms are derived for the cases when there is structural modeling error as well as when the a priori statistics of identified parameters, and plant and measurement noise, are incorrectly specified. The... View full abstract»

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  • Macroeconomic modeling for control

    Publication Year: 1974, Page(s):862 - 873
    Cited by:  Papers (1)
    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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  • A self-tuning predictor

    Publication Year: 1974, Page(s):848 - 851
    Cited by:  Papers (15)
    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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  • Coupled design of test signals, sampling intervals, and filters for system identification

    Publication Year: 1974, Page(s):748 - 752
    Cited by:  Papers (18)
    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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  • Biological modeling with variable compartmental structure

    Publication Year: 1974, Page(s):922 - 926
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (560 KB)

    Many biological processes such as water balance and temperature regulation may be modeled by a variable-structure compartmental system of ordinary differential equations. In some cases the system is naturally bilinear, and in others the bilinear system may be a valid approximation of a complex nonlinear process. Tracer dynamics and associated methodology, which can be used to realize certain prope... 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 (22)
    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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  • Stochastic theory of minimal realization

    Publication Year: 1974, Page(s):667 - 674
    Cited by:  Papers (175)
    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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Aims & Scope

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