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Automatic Control, IEEE Transactions on

Issue 3 • Date March 1989

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Displaying Results 1 - 25 of 29
  • Asymptotically efficient adaptive allocation schemes for controlled i.i.d. processes: finite parameter space

    Publication Year: 1989 , Page(s): 258 - 267
    Cited by:  Papers (10)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (645 KB)  

    The authors consider a controlled i.i.d. (independently identically distributed) process whose distribution is parametrized by an unknown parameter theta belonging to some known parameter space Theta , and a one-step reward associated with each pair of control and the following state of the process. The objective is to maximize the expected value of the sum of one-step rewards over an infinite horizon. By introducing the loss associated with a control scheme, it is shown that the problem is equivalent to minimizing this loss. Uniformly good adaptive control schemes are defined and emphasized. A lower bound on the loss associated with any uniformly good control scheme is developed. Finally, an adaptive control scheme is constructed whose loss equals the lower bound, and is therefore asymptotically efficient.<> View full abstract»

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  • On the design of linear multivariable feedback systems via constrained nondifferentiable optimization in H/sup infinity / spaces

    Publication Year: 1989 , Page(s): 268 - 276
    Cited by:  Papers (43)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (791 KB)  

    The design discussed is of linear, lumped, time-invariant, multivariable feedback systems, subject to various frequency and time-domain performance specifications. The approach is based on the use of stabilizing controller parametrizations which result in the formulation of feedback system design problems as convex, nondifferentiable optimization problems. These problems are solvable by recently developed nondifferentiable optimization algorithms for the constrained minimization of regular, uniformly locally Lipschitz continuous functions in R/sup N/.<> View full abstract»

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  • Almost disturbance decoupling with internal stability

    Publication Year: 1989 , Page(s): 277 - 286
    Cited by:  Papers (26)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (988 KB)  

    The almost disturbance decoupling problem with internal stability is solved in terms of the geometric concepts of linear systems theory. The solution gives necessary and sufficient conditions for the existence of a dynamic output feedback controller such that in the closed-loop system the disturbances are quenched, say in the H/sup infinity /-sense, up to any degree of accuracy while maintaining a stable system matrix.<> View full abstract»

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  • A generalization of Kharitonov's theorem; Robust stability of interval plants

    Publication Year: 1989 , Page(s): 306 - 311
    Cited by:  Papers (87)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (477 KB)  

    The robust stability problem is considered for interval plants, in the case of single input (multioutput) or single output (multi-input) systems. A necessary and sufficient condition for the robust stabilization of such plants is developed, using a generalization of V. L. Kharitonov's theorem (1978). The generalization given provides necessary and sufficient conditions for the stability of a family of polynomials delta (s)=Q/sub 1/(s)P/sub 1/(s)+ . . . +Q/sub m/(s)P/sub m/(s), where the Q/sub i/ are fixed and the P/sub i/ are interval polynomials, the coefficients of which are regarded as a point in parameter space which varies within a prescribed box. This generalization, called the box theorem, reduces the question of the stability of the box, in parameter space to the equivalent problem of the stability of a prescribed set of line segments. It is shown that for special classes of polynomials Q/sub i/(s) the set of line segments collapses to a set of points, and this version of the box theorem in turn reduces to Kharitonov's original theorem.<> View full abstract»

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  • Identification of a class of nonlinear state-space models using RPE techniques

    Publication Year: 1989 , Page(s): 312 - 316
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    The RPE (recursive prediction error) method in state-space form is developed in the nonlinear systems and extended to include the exact form of a nonlinearity, thus enabling structure preservation for certain classes of nonlinear systems. Both the discrete and the continuous-discrete versions of the algorithm in an innovations model are investigated, and a nonlinear simulation example shows a quite convincing performance of the filter as combined parameter and state estimator.<> View full abstract»

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  • Failure detection and identification

    Publication Year: 1989 , Page(s): 316 - 321
    Cited by:  Papers (121)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (591 KB)  

    Using the geometric concept of an unobservability subspace, a solution is given to the problem of detecting and identifying control system component failures in linear, time-invariant systems. Conditions are developed for the existence of a causal, linear, time-invariant processor that can detect and uniquely identify a component failure, first for the case where components can fail simultaneously, and then for the case where they fail only one at a time. Explicit design algorithms are provided when these conditions are satisfied. In addition to time-domain solvability conditions, frequency-domain interpretations of the results are given, and connections are drawn with results already available in the literature.<> View full abstract»

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  • Almost-sure convergence of adaptive algorithms by projections

    Publication Year: 1989 , Page(s): 325 - 327
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (230 KB)  

    A convergence proof is discussed for the normalized least-mean-square (LMS) algorithm for ergodic inputs. The approach is based on interpreting the algorithm as a sequence of relaxed projection operators by which the key contraction property is derived. The proof technique is strongly motivated by physical intuition, and provides additional insight into LMS-type algorithms under ergodic inputs. Embedded in the development is a slight generalization to a random time-varying gain parameter. This allows the incorporation of variations such as the LMS and signed LMS algorithms.<> View full abstract»

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  • Recursive identification of overparametrized systems

    Publication Year: 1989 , Page(s): 327 - 331
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    A recursive identification algorithm based on extended least squares is proposed to deal with the contingency of overparametrization. The algorithm is relatively simple compared to those involving online order determination, being based on adaptively introducing suitable excitation into the algorithm to avoid ill-conditioning. In the case of extended-least-squares-based adaptive estimation, then the regressors are appropriately stochastically perturbed. The algorithm is shown to converge to a uniquely defined signal model with any pole-zero cancellations at the origin.<> View full abstract»

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  • Application of spectral factorization to the linear discrete-time fixed-point smoothing problem

    Publication Year: 1989 , Page(s): 333 - 335
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB)  

    An explicit expression for the minimum-variance steady-state fixed-point smoothing estimate of the output of linear, discrete-time invariant system is obtained in terms of the measurement spectral factor. The filtered estimate of the states of the system is first derived by finding the spectral factor for the power density matrix of the measurement signal. The z-transform of the time-varying gain matrix, which produces the optimal smoothing estimate by multiplying the innovations process of the Kalman filter, is also obtained in terms of this factor. The results are easily extended to cases with colored measurement and driving noise signals; they are particularly simple to apply in the single-input-single-output case.<> View full abstract»

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  • Stochastic task selection and renewable resource allocation

    Publication Year: 1989 , Page(s): 335 - 339
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB)  

    A class of renewable-resource-allocation problems is studied for the processing of dynamically arriving tasks with deterministic deadlines. The model presented explicitly considers time available, time required, resources available, resources required, stochastic arrivals of multiple types of tasks, importance of tasks, timeliness of processing, and accuracy of resource allocation. After state augmentation, the problem becomes a Markovian decision problem, and can be solved, at least in principle, by using a stochastic dynamic programming (SDP) method. Effects of key system parameters on optimal decisions are investigated and analyzed through numerical examples.<> View full abstract»

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  • On global stability of adaptive systems using an estimator with parameter freezing

    Publication Year: 1989 , Page(s): 343 - 346
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (287 KB)  

    The results of R. Kosut and B. Friedlander (1985) on robust global stability of direct adaptive controllers using an integral adaptation law are extended to the case where the adaptation algorithm includes a parameter freezing mechanism, i.e. the control parameters are held constant at certain time intervals. The authors' main concern is to propose an estimator with freezing capabilities which preserve the property needed for the global stability analysis, namely, that it defines a passive operator. In an adaptive control context, the additional degree of freedom provided by the freezing imposes no further assumptions for global stability. A crucial requirement for the analysis is that the number of freezing intervals is finite.<> View full abstract»

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  • A globally convergent pole placement indirect adaptive controller

    Publication Year: 1989 , Page(s): 353 - 356
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (355 KB)  

    A pole displacement indirect adaptive control algorithm is discussed for discrete-time linear deterministic plants with arbitrary zeros. The global convergence of the resulting closed-loop control system is achieved subject to the assumptions that the plant order and a nonzero lower bound on its degree of controllability are known. The problem of controllability of the plant model estimate is handled by using both a parameter correction and time-varying nonlinear feedback. A key property of the algorithm is that the plant estimate reaches a reasonable degree of controllability in a finite time, after which the parameter correction and the nonlinear feedback are no longer used.<> View full abstract»

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  • Robust pole placement direct adaptive control

    Publication Year: 1989 , Page(s): 356 - 359
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB)  

    A pole-placement direct adaptive control for not necessarily minimum-phase plants is presented, which is robust with respect to unmodeled dynamics and bounded disturbances. The robustness is achieved by using both a normalized least-squares algorithm with dead zone and appropriate nonlinear feedback. The resulting closed-loop system is shown to be globally stable subject to standard assumptions.<> View full abstract»

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  • A novel approach to the explicit pole assignment self-tuning controller design

    Publication Year: 1989 , Page(s): 359 - 363
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (419 KB)  

    A recursive algorithm for the controller design phase of the adaptive pole assignment controller is presented. Compared to other pole-assignment adaptive controllers, the computation time to get the controller parameters is drastically reduced and the numerical stability of the controller parameters is increased. If persistent excitation is imposed, the system poles will be located at the desired position in the steady state and the global stability of the system can be easily obtained.<> View full abstract»

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  • Central tendency adaptive pole assignment

    Publication Year: 1989 , Page(s): 363 - 367
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (383 KB)  

    The concept of central-tendency adaptive control for achieving minimum variance objectives, proposed by the authors in a companion paper (1989), is applied to adaptive pole assignment. At any iteration, given plant parameter estimate and their uncertainty, a controller is designed which is most likely to achieve the pole assignment objectives. Simulations show a factor-of-100 improvement in transient response over certainty equivalent adaptive pole assignment schemes, for one example.<> View full abstract»

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  • Central tendency minimum variance adaptive control

    Publication Year: 1989 , Page(s): 367 - 371
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB)  

    The authors propose designing indirect adaptive controllers using measures of central tendency of the a posteriori probability function of the control for parameters. That is, given a knowledge of plant uncertainty at each time instant from estimation algorithms, and a controller design rule, controller parameters are sought which maximize the likelihood of achieving the control objectives. The particular case of adaptive minimum variance control is studied in detail.<> View full abstract»

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  • ARX modeling of controlled ARMAX plants and LQ adaptive controllers

    Publication Year: 1989 , Page(s): 371 - 375
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (413 KB)  

    Conditions under which controlled ARMAX (autoregressive moving-average models with auxiliary inputs) plants can be described by ARX (autoregressive models with auxiliary inputs) models are studied. Among all possible ARX models, the ones that can be correctly used in long-range LQ (linear quadratic) adaptive control are characterized. Within this framework, LQ adaptive controllers embodying standard recursive least-squares identifiers are singled out and shown to have equilibrium points solving related underlying LQ control problems for the true ARMAX plant.<> View full abstract»

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  • Combined sequence of Markov parameters and moments in linear systems

    Publication Year: 1989 , Page(s): 379 - 382
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (361 KB)  

    The combined sequence of Markov parameters and moments in linear systems is discussed. This sequence is shown to be generated by a linear feedback shift register. Application to the minimal degree partial realization from a mixture of any number of Markov parameters and moments is considered. Central in this particular realization problem is the extension of a Toeplitz partial behavior matrix. This is accomplished on the basis of the algebraic theory of Iohvidov indexes for Toeplitz matrices.<> View full abstract»

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  • Comments on "Parameter information content of measurable signals in direct adaptive control" [with reply]

    Publication Year: 1989 , Page(s): 382 - 383
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (187 KB)  

    The commenter shows that the parameter adjustment procedure proposed by J.M. Krause and P.P. Khargonekar (see ibid., vol.AC-32, p.802-10, Sep. 1987) reduces, after sufficiently exciting signals have been obtained, to a standard least-squares algorithm with a linear time-invariant filter. In reply, Krause and Khargonekar acknowledge that the commenter has demonstrated a valid and different interpretation of their two-stage adjustment law.<> View full abstract»

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  • Comments on "An algorithm for a solution of a stochastic adaptive linear quadratic optimal control problem

    Publication Year: 1989 , Page(s): 383 - 384
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (156 KB)  

    It is shown that there is an inconsistency in the derivation of the adaptive estimation equations by R. Rishel and L. Harris (see ibid., vol.AC-31, p.1165-70, Dec. 1986). An extra condition that is required is noted.<> View full abstract»

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  • Comments on "Estimation using a multirate filter

    Publication Year: 1989
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (63 KB)  

    The present author offers precedents for use of the Bar-Itzhack filter formulation, as recently recast in a multirate parallel Kalman filter framework discussed by D. Andrisani, II and C.-F. Gau (see ibid., vol.AC-32, p.653-6, Jul. 1987).<> View full abstract»

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  • An improved adaptive control for robust adaptation

    Publication Year: 1989 , Page(s): 339 - 343
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    An adaptive control law consisting of an integral and proportional adaptation is suggested. It is shown that the addition of the proportional adaptation term to the control law improves the performance of the adaptive system. Although this is done in the context of a first-order system, it is believed that this may also be the case for higher-order systems. The scalar case is only discussed. Simulation results are presented to complement the theoretical developments View full abstract»

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  • Discrete-time adaptive control of systems consisting of known and unknown subsystems

    Publication Year: 1989 , Page(s): 375 - 379
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB)  

    A method is presented for the discrete-time adaptive control of systems resulting from the cascade, parallel, and feedback interconnection of two subsystem pairs, each of which consists of a cascade of known and unknown blocks. Such interconnection can realistically represent physical systems to be controlled. Partial plant knowledge is incorporated into the adaptive algorithm so as to reduce the number of parameters to be identified View full abstract»

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  • On systems with non-Markovian regime changes

    Publication Year: 1989 , Page(s): 346 - 349
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    Jump models have been proposed for a wide variety of applications from fault-tolerant control to power network transient analysis and multitarget tracking. However, most available results are limited to Markovian transitions, which excludes systems with rates dependent on the time elapsed since the last transition; that is, typically, the burn-in and aging phenomena. A non-Markovian model is proposed and its use for the synthesis of feedback regulators is discussed View full abstract»

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  • LQG control with an H performance bound: a Riccati equation approach

    Publication Year: 1989 , Page(s): 293 - 305
    Cited by:  Papers (278)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1108 KB)  

    An LQG (linear quadratic Gaussian) control-design problem involving a constraint on H disturbance attenuation is considered. The H performance constraint is embedded within the optimization process by replacing the covariance Lyapunov equation by a Riccati equation whose solution leads to an upper bound on L2 performance. In contrast to the pair of separated Riccati equations of standard LQG theory, the H-constrained gains are given by a coupled system of three modified Riccati equations. The coupling illustrates the breakdown of the separation principle for the H-constrained problem. Both full- and reduced-order design problems are considered with an H attenuation constraint involving both state and control variables. An algorithm is developed for the full-order design problem and illustrative numerical results are given 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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Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame