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Automatic Control, IEEE Transactions on

Issue 3 • Date June 1975

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

    Page(s): 0
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    Freely Available from IEEE
  • Editorial: Some goals for the transactions

    Page(s): 309
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    Freely Available from IEEE
  • On the calculation of matrix polynomials

    Page(s): 435 - 437
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    The purpose of this note is to prove a theorem which permits the calculation of the vector b without the necessity of transforming the matrix A into the Jordan form for the Cayley-Hamilton theorem. The only requirement is the calculation of the characteristic polynomial of the matrix A, which may be easily done using the existing computational procedures. The author includes a computer program listing of a subroutine that calculates the coefficients of the n-dimensional vector b. This subroutine makes use of certain standard IBM subroutines, as SMPY, GMPRD, GMSUB, and GMADD, from the IBM 1130 Scitific Subroutine Package, and utilized another subroutine CHEQ described by the author in ibid., vol AC-20, pp. 134-135, Feb. 1975, that calculates the coefficients of the characteristic polynomial of the matrix A. View full abstract»

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  • Comments on "Parameter identification and control of linear discrete-time systems"

    Page(s): 442 - 443
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    A new proof of convergence of the stochastic approximation algorithm for parameter identification of closed-loop linear discrete-time control systems is proposed. This algorithm relates very effectively in terms of a sufficient condition the stability properties of the closed-loop system with the convergence of the identification algorithms, which were previously treated independently. View full abstract»

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  • Comments on "Luenberger's canonical form revisited

    Page(s): 444 - 445
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    Results similar to those presented in the above paper have previously been developed for a slightly different version of Luenberger's canonical form. These results are summarized herein to provide an alternate canonical form that can be used for system identification. For certain applications, such as observer design, the canonical form presented is particularly well suited. Both canonical forms provide the same number of undefined parameters. View full abstract»

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  • Comments on "Order assumption and singularity of information matrix for pulse transfer function models"

    Page(s): 445 - 447
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    In this note it is investigated how the model order influences the singularity of the information matrix and how this singularity is related to identifiability of the system. The propositions given in [5] are made more stringent, generalized, and proven. View full abstract»

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  • [Back cover]

    Page(s): 0
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    Freely Available from IEEE
  • Decoupling and data sensitivity

    Page(s): 338 - 344
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    For the perturbed systemdot{x} = (A_{0} + delta A)x + (B_{0} + delta B)u, z_{i} = D_{i}x, iin k, constructive necessary and sufficient conditions are given, that the decoupling problem, when solved via extension for the nominal dataA_{0}, B_{0}, D_{i}, iin k, remains solved when the perturbationsdelta Aanddelta Bare sufficiently small. View full abstract»

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  • Economic optimization of an aquaculture facility

    Page(s): 310 - 319
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    This paper describes mathematical models for different components of aquaculture and applies optimization theory to the design and operation of an aquaculture facility. The state variables are the number of animals in a batch, their average weight, and their cost. The control variables relate to the water temperature, the water recirculation and waste treatment, the space per animal, the amount of food per animal, and the kind of food. Optimization techniques are applied to the operation of an aquaculture facility, to raise lobsters. Some sample numerical results are presented, and the interaction of these theoretical results with practical considerations is discussed. View full abstract»

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  • Determination of matrix transfer function in the form of matrix fraction from input-output observations

    Page(s): 392 - 396
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    This short paper concerns the identification of a linear time-invariant discrete system represented by a matrix transfer function in the form of a matrix fraction. The relations between external and internal descriptions are discussed, and all matrix transfer functions satisfying given input-output observations are determined. View full abstract»

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  • Near-optimal state estimation for interconnected systems

    Page(s): 348 - 351
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    A new algorithm is proposed for estimating the state of a nonlinear stochastic system when only noisy observations of the state are available. The state estimation problem is formulated as a modal-trajectory, maximum likelihood estimation problem. The resulting minimization problem is analogous to the nonlinear tracking problem in optimal control theory. By viewing the system as an interconnection of lower-dimension subsystems and applying the so-called ε-coupling technqiue, which originated in the study of sensitivity of control systems to parameter variations, a near-optimal state estimation algorithm is derived which has the properties that all computations can be performed in parallel at the subsystem level and only linear equations need be solved. The principal attraction of the method is that significant reductions in the computational requirements relative to other approximate algorithms can be achieved when the system is large-dimensional. View full abstract»

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  • The stabilizing solution of the discrete algebraic riccati equation

    Page(s): 396 - 399
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    This short paper extends the existence theory of the stabilizing solution of the discrete algebraic Riccati equation. The main result provides necessary and sufficient conditions for the existence of such a solution, free of any a priori conditions on the problem data. For the special case of the optimal regulator problem, standard results are recovered as special cases. View full abstract»

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  • Unbiased parameter estimation by means of autocorrelation functions

    Page(s): 368 - 372
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    A new method for obtaining an on-line unbiased estimate of the parameter vector of linear systems in the presence of additive uncorrelated output noise is described. The method, which is based on the equation error, is developed for continuous variables and then formulated both for continuous and discrete representations. Instead of the conventional least squares approach, the autocorrelation function of the error serves as the cost function to be minimized. It is shown that for comparatively wide-band noise, this cost function yields unique and practically unbiased estimates. On-line identification from system input and output is feasible. Bias suppression as a function of the time-delay in the cost function is demonstrated by numerical examples. Convergence of the estimates is demonstrated by means of simulated continuous and discrete examples. View full abstract»

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  • Time optimal behavior of human saccadic eye movement

    Page(s): 345 - 348
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    Optimal control theory takes into account constraints such as energy and time economies which are relevant to the understanding of biological design. The versional eye tracking system responsible for the extremely rapid and precise movements called saccades, which occur, for example, during reading, seemed a likely biological system in which to test for time optimality. A homeomorphic detailed physiological model was constructed based on quantitative muscle, neuronal and oculomotor characteristcs. It is a sixth-order nonlinear representation which considers reciprocal innervation and the asymmetrical force-velocity relationship of the agonist-antagonist muscle pair that moves the eye. Simulations were done by digital computer, and responses of the model to first-, second-, and third-order time optimal control signals were observed; the major portions of the response trajectories were essentially the same. The model response was then compared with measured human saccadic eye movements, and it was found that this experimental data agreed most completely with the model driven by first-order time optimal control signals. Additionally, electromyographic studies in man and neurophysiological experiments in animals agree in showing that the nervous controller signals during saccades are also of the first-order type. Thus, we can conclude that the saccadic eye movements studied are accurately depicted by a model that yields time optimal responses. View full abstract»

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  • Control of linear discrete-time stochastic dynamic systems with multiplicative disturbances

    Page(s): 388 - 392
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    Multiplicative random disturbances frequently occur in economic modeling. The money multiplier in a simple monetary macroeconomic model is treated as a random variable in this paper. The optimal control law is derived, and some consequences of erroneous modeling of the random disturbance are exhibited by simulation. View full abstract»

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  • Convergence of discretization procedures in dynamic programming

    Page(s): 415 - 419
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    The computational solution of discrete-time stochastic optimal control problems by dynamic programming requires, in most cases, discretization of the state and control spaces whenever these spaces are infinite. In this short paper we consider a discretization procedure often employed in practice. Under certain compactness and Lipschitz continuity assumptions we show that the solution of the discretized algorithm converges to the solution of the continuous algorithm, as the discretization grids become finer and finer. Furthermore, any control law obtained from the discretized algorithm results in a value of the cost functional which converges to the optimal value of the problem. View full abstract»

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  • A prefiltering version of the Kalman filter with new numerical integration formulas for Riccati equations

    Page(s): 378 - 381
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    A prefiltering version of the Kalman filter is derived for both discrete and continuous measurements. The derivation consists of determining a single discrete measurement that is equivalent to either a time segment of continuous measurements or a set of discrete measurements. This prefiltering version of the Kalman filter easily handles numerical problems associated with rapid transients and ill-conditioned Riccati matrices. Therefore, the derived technique for extrapolating the Riccati matrix from one time to the next constitutes a new set of integration formulas which alleviate ill-conditioning problems associated with continuous Riccati equations. Furthermore, since a time segment of continuous measurements is converted into a single discrete measurement, Potter's square root formulas can be used to update the state estimate and its error covariance matrix. Therefore, if having the state estimate and its error covariance matrix at discrete times is acceptable, the prefilter extends square root filtering with all its advantages, to continuous measurement problems. View full abstract»

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  • Optimal continuous finite preview problem

    Page(s): 362 - 365
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    This short paper deals with the preview problem, in which a controller can use future information as well as present and past information in deciding the control. The problem of following command signals is considered for the continuous time system. It is assumed that the controller can make use of the finite preview information with respect to command signal from the present timetup to tlatime units in the future. tlais called the preview length and usuallyt_{la} < T, the duration of the problem, which distinguishes the present problem from the optimal tracking problem. It is shown how to utilize the local future information obtained by finite preview to minimize an optimality criterion evaluated over the problem duration. An example is given to show advantages of making use of future information and the existence of an effective preview length. View full abstract»

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  • Ordered sequential filtering for finite dimensional systems with distributed observations

    Page(s): 351 - 354
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    This short paper treats the topic of suboptimal linear estimation for systems which have a finite dimensional state vector but a distributed set of observations. Such systems are of some practical interest, and are indeed considerably easier to work with than most distributed parameter systems. The method proposed here is that a filter structure of linear form, driven by a statistic which is a weighted integral of the distributed observation, be used to generate estimates of the state of the system. The filter parameters, and the weighting function for the integral are selected so that the estimate is unbiased and results in minimum mean-square error, subject to the structural constraints. View full abstract»

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  • Redundancy in team problems

    Page(s): 439 - 440
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    We study here a class of problems with multiple decision makers. In some such problems one or more of the decision makers ignores seemingly useful information. The purposes of the present note is to introduce this new singularity. View full abstract»

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  • Stability analysis and simulation of a first-order chopper pulsewidth modulated (PWM) system

    Page(s): 420 - 422
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    Asymptotic stability in the large (ASIL) of a first-order pulsewidth modulated (PWM) system as encountered in thyristor chopper circuits is investigated. Theoretical predictions are verified by computer simulation. View full abstract»

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  • L_{2} -stability of a class of nonstationary feedback systems with dynamical nonlinear subsystems

    Page(s): 412 - 415
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    A class of feedback systems, consisting of dynamical non-linear subsystems which arise in many diverse control applications, is analyzed for L2-stability. It is shown that, although a transformation of these systems to the familiar Lur'e configuration does not seem to be possible, a one-to-one correspondence may be effected between the stability properties of these and the Lur'e systems. Interesting stability criteria are developed by exploiting this characteristic. View full abstract»

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  • On the numerical solution of the generalized eigenproblem

    Page(s): 437 - 439
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    An iterative method is suggested for the solution of the generalized eigenproblem. The iteration is shown to possess cubic order of convergence in the case of distinct eigenvalues. The algorithm appears at its best advantage when good starting values are available; engineering applications where this is so are briefly discussed. View full abstract»

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  • Optimum inventory and product quality control with deterministic and stochastic deterioration--An application of distributed parameters control systems

    Page(s): 407 - 412
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    Inventory models with deterministic and stochastic deterioration rates are given. The first model, assuming deterministic deterioration rates, is a hyperbolic equation while the second one assuming a stochastic deterioration rate is reduced to a parabolic equation of the second order. Optimization of these in inventory models when costs are quadratic yields linear feedback replenishment policies. This short paper provides an analytic solution to both problems. The importance of such inventory models is to be found when the demand and value of stored products is also dependent on their quality. 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