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Automatic Control, IEEE Transactions on

Issue 5 • Date May 1995

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Displaying Results 1 - 25 of 29
  • Comments on "A modification and the Tustin approximation" with a concluding proposition

    Page(s): 942 - 944
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (341 KB)  

    In the original paper (K.B. Janiszowski, ibid., vol. 38, no. 8, p. 1313-16, 1993) there is presented a modification of the Tustin approximation. The author argues that the justification of this modification, by means of three examples, is not convincing, because the choice of the examples is questionable and some calculations are not sufficiently accurate. It is shown that some good properties of the proposed modification can be justified by using the Tustin approximation of a continuous-time (CT) model for the discrete-time (DT) system. It is stressed that the proposed modification has only a limited value, since from application point of view the use of CT models is more reasonable. As the conclusion the DT controller design procedure by using CT methods is proposed.<> View full abstract»

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  • Continuation methods for solving modified discrete-time algebraic Riccati equations

    Page(s): 920 - 924
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (428 KB)  

    It is well known that the continuation methods have been successfully applied to solve polynomial systems and fixed point problems, etc. In this paper, we consider a discrete-time algebraic Riccati equation with an admissible, low rank, and symmetric perturbation. Our attention is directed primarily to this modified discrete-time algebraic Riccati equation and the numerical method for its solution based on proceeding along the continuation path View full abstract»

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  • Krein space approach to H mixed sensitivity minimization for a class of infinite dimensional systems

    Page(s): 865 - 881
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1272 KB)  

    Motivated by the computation of the H optimal performance and optimal mixed sensitivity for a class of infinite dimensional systems, the author considers the explicit computation of the norm and minimal symbols of a class of “Hankel plus Toeplitz” type operators with irrational symbols using the Krein space approach. The author shows how to explicitly compute the norm and parameterize all the minimal symbols. The results are used to obtain a complete solution to the H optimal mixed sensitivity synthesis problem for a class of infinite dimensional systems: an explicit formula for computing the H optimal performance and explicit parameterization of all optimal and suboptimal mixed sensitivities. An illustrative example is given View full abstract»

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  • Discounted linear exponential quadratic Gaussian control

    Page(s): 968 - 971
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB)  

    In this note, we describe a recursive formulation of discounted costs for a linear quadratic exponential Gaussian linear regulator problem which implies time-invariant linear decision rules in the infinite horizon case. Time invariance in the discounted case is attained by surrendering state-separability of the risk-adjusted costs View full abstract»

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  • On delay-independent stability of large-scale systems with time delays

    Page(s): 930 - 933
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    A new criterion for delay-independent stability of linear large scale time-delay systems is deduced by employing an improved Razumikhin-type theorem and the m-matrix properties. An illustrative example is given to demonstrate the superiority of the obtained results to those in the literature View full abstract»

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  • A linear programming approach to large-scale linear optimal control problems

    Page(s): 971 - 977
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (704 KB)  

    This paper considers the solution of large-scale linear optimal control problems subject to linear control and state constraints by application of a linear programming (LP-) based methodology. The proposed algorithm is based on a particular LP-method that is suitably modified and adapted to the structure of the considered discrete-time dynamic problem to keep the computation time low and efficiently store the arising large, but sparse, matrices. The efficiency of the approach is demonstrated via a practical example arising in the field of traffic control in data-communication networks. The algorithm is shown to solve problems involving several thousands of variables in few seconds on a workstation thus enabling real-time optimal control for a number of potential practical applications View full abstract»

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  • A comment on “Decentralized stabilization of large scale interconnected systems with delays”

    Page(s): 914 - 916
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    Hu claims new results in the above mentioned paper (ibid. vol.39, no.1, p.180-2 (1994)) regarding decentralized stabilization of large scale interconnected systems with delays. This note shows that the results presented in Theorems 1 and 2 and Corollaries 1 and 2 apply only to a very restrictive class of systems for which the number of inputs and outputs is equal to the number of states. An alternative stability condition is provided, which improves the existing one View full abstract»

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  • Higher order approximate feedback linearization about a manifold for multi-input systems

    Page(s): 833 - 840
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB)  

    Considers the problem of approximately feedback linearizing a multi-input nonlinear system around the equilibrium manifold ε while making the error terms be of highest order on ε. Necessary and sufficient conditions are given for approximately feedback linearizing the system around ε with error terms of order ρ on ε. A simple multi-input example is given to illustrate the higher order approximate feedback linearization procedure View full abstract»

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  • Identifiability of minimal, stable, rational, causal systems using second-order output cyclic spectra

    Page(s): 959 - 962
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    In this paper, the (blind) identifiability of systems using the second-order output cyclic spectra is considered. It is shown that the class of minimal, stable, rational causal (MSRC) systems is not identifiable, and the identification is limited by a nontrivial ambiguity associated with the so-called cyclic all-pass factor. The largest subclass of MSRC systems that ensures the unique identification is shown to be the set of MSRC systems that do not have special uniformly spaced maximum phase zeros View full abstract»

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  • Halley's method for the matrix sector function

    Page(s): 944 - 949
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (548 KB)  

    The matrix n-sector function is a generalization of the matrix sign function; it can be used to determine the number of eigenvalues of a matrix in a specific sector of the complex plane and to extract the eigenpairs belonging to this sector without explicitly computing the eigenvalues. It is known that Newton's method, which can be used for computing the matrix sign function, is not globally convergent for the matrix sector function. The only existing algorithm for computing the matrix sector function is based on the continued fraction expansion approximation to the principal nth root of an arbitrary complex matrix. In this paper, we introduce a new algorithm based on Halley's generalized iteration formula for solving nonlinear equations. It is shown that the iteration has good error propagation properties and high accuracy. Finally, we give two application examples and summarize the results of our numerical experiments comparing Newton's, the continued fraction, and Halley's method View full abstract»

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  • Unbiased identification of systems with nonparametric uncertainty

    Page(s): 933 - 936
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB)  

    The set-membership identification of systems with parametric and nonparametric uncertainty is studied. The bias induced by the additive noise is eliminated by using the bias-eliminated least squares method proposed previously by us (1991). A prefilter is connected to the input terminal of the system, so that some zeros are inserted to the system. By using the information obtained from these known zeros, the bias induced by the additive noise is eliminated View full abstract»

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  • Adaptive control of a class of nonlinear discrete-time systems using neural networks

    Page(s): 791 - 801
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (880 KB)  

    Layered neural networks are used in a nonlinear self-tuning adaptive control problem. The plant is an unknown feedback-linearizable discrete-time system, represented by an input-output model. To derive the linearizing-stabilizing feedback control, a (possibly nonminimal) state-space model of the plant is obtained. This model is used to define the zero dynamics, which are assumed to be stable, i.e., the system is assumed to be minimum phase. A linearizing feedback control is derived in terms of some unknown nonlinear functions. A layered neural network is used to model the unknown system and generate the feedback control. Based on the error between the plant output and the model output, the weights of the neural network are updated. A local convergence result is given. The result says that, for any bounded initial conditions of the plant, if the neural network model contains enough number of nonlinear hidden neurons and if the initial guess of the network weights is sufficiently close to the correct weights, then the tracking error between the plant output and the reference command will converge to a bounded ball, whose size is determined by a dead-zone nonlinearity. Computer simulations verify the theoretical result View full abstract»

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  • Hybrid force/position control for manipulators with motor dynamics using a sliding-adaptive approach

    Page(s): 963 - 968
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB)  

    Based on a decomposition of the rigid robot system with motor dynamics, a novel sliding-adaptive controller is developed which can achieve robustness to parameter variations in both manipulator and motor. When the system is in sliding mode, force, position, and redundant joint velocity errors will approach zero irrespective of parametric uncertainties. Unlike conventional sliding techniques which are only robust to matched uncertainties, the proposed sliding method is robust to both matched and mismatched uncertainties. Hence the scope of applications of sliding mode method can be broadened to nonlinear systems with mismatched parameter variations. No joint acceleration measurement is needed View full abstract»

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  • A robust periodic pole assignment algorithm

    Page(s): 890 - 894
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (456 KB)  

    In this note a robust periodic pole assignment algorithm is proposed for linear, time-invariant, discrete-time systems. The condition numbers of the eigenvector matrices of the closed-loop system are assumed as a robustness measure and a periodic state-feedback law is deduced by the minimization of the condition numbers associated to the eigenvectors of the monodromy matrix of the closed-loop system. The proposed periodic pole assignment algorithm has been tested on a number of examples, giving satisfactory results View full abstract»

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  • Stability of acyclic multiclass queueing networks

    Page(s): 916 - 919
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (420 KB)  

    In this paper we study multiclass queueing networks with fluid arrival streams and service processes. Assuming that the arrival rate does not exceed the network capacity, we deduce stability of the network using the tools of ergodic theory. We show that the distributions of the process converge to a unique steady state value and that convergence takes place at a geometric rate under appropriate moment conditions View full abstract»

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  • A convex characterization of gain-scheduled H controllers

    Page(s): 853 - 864
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (944 KB)  

    An important class of linear time-varying systems consists of plants where the state-space matrices are fixed functions of some time-varying physical parameters θ. Small gain techniques can be applied to such systems to derive robust time-invariant controllers. Yet, this approach is often overly conservative when the parameters θ undergo large variations during system operation. In general, higher performance can be achieved by control laws that incorporate available measurements of θ and therefore “adjust” to the current plant dynamics. This paper discusses extensions of H synthesis techniques to allow for controller dependence on time-varying but measured parameters. When this dependence is linear fractional, the existence of such gain-scheduled H controllers is fully characterized in terms of linear matrix inequalities. The underlying synthesis problem is therefore a convex program for which efficient optimization techniques are available. The formalism and derivation techniques developed here apply to both the continuous- and discrete-time problems. Existence conditions for robust time-invariant controllers are recovered as a special case, and extensions to gain-scheduling in the face of parametric uncertainty are discussed. In particular, simple heuristics are proposed to compute such controllers View full abstract»

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  • Passivity-based control of nonlinear flexible multibody systems

    Page(s): 910 - 914
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB)  

    In this paper, global asymptotic stability of a class of nonlinear multibody flexible space structures under certain dissipative compensation is established. Furthermore, for an important subclass of such systems, the stability is shown to be robust to certain types of actuator and sensor nonlinearities. The results are applicable to robust stabilization of a wide class of systems, including flexible space structures and manipulators with articulated flexible appendages. The stability proofs use the Lyapunov approach and exploit the inherent passivity of such systems View full abstract»

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  • Composite modeling of transfer functions

    Page(s): 820 - 832
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1068 KB)  

    The problem under consideration is how to estimate the frequency function of a system and the associated estimation error when a set of possible model structures is given and then one of them is known to contain the true system. The “classical” solution to this problem is to, first, use a consistent model structure selection criterion to discard all but one single structure, second, estimate a model in this structure and, third, conditioned on the assumption that the chosen structure contains the true system, compute an estimate of the estimation error. For a finite data set, however, one cannot guarantee that the correct structure is chosen, and this “structural” uncertainty is lost in the previously mentioned approach. In this contribution a method is developed that combines the frequency function estimates and the estimation errors from all possible structures into a joint estimate and estimation error. Hence, this approach bypasses the structure selection problem. This is accomplished by employing a Bayesian setting. Special attention is given to the choice of priors. With this approach it is possible to benefit from a priori information about the frequency function even though the model structure is unknown View full abstract»

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  • Model reduction by matching Markov parameters, time moments, and impulse-response energies

    Page(s): 949 - 953
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB)  

    This paper presents a simple procedure for constructing reduced-order models that match some Markov parameters and time moments of an original system as well as the energies of its impulse response and of other combinations of the system modes. In this way, the stability of the reduced model of a stable system is ensured View full abstract»

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  • Expansion of det(A+B+C) and robustness analysis of discrete-time state-space systems

    Page(s): 936 - 942
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (420 KB)  

    In this paper, the expansion of det(A+B+C) is given. The robustness problem for discrete-time state-space systems with uncertain parameters is investigated by applying the Schur stability theory of interval polynomials. A stability robustness criterion for the uncertain systems is derived. Illustrative examples are presented View full abstract»

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  • Prediction of track purity and track accuracy in dense target environments

    Page(s): 953 - 959
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (732 KB)  

    This note is concerned with performance prediction of multiple-target tracking systems, particularly in data-rich, high-target-density environments. Two simple but useful expressions are described: (i) the exponential law for predicting average probability of correct data association, and (ii) the linear-times-exponential law for calculating the effective measurement error variances with possible data misassociation. Estimation of two key multiple-target tracking performance measures, i.e., track purity and track accuracy, are then derived using these two laws View full abstract»

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  • Hierarchical production and setup scheduling in stochastic manufacturing systems

    Page(s): 924 - 930
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (652 KB)  

    This paper is concerned with an asymptotic analysis of hierarchical production and setup scheduling in a stochastic manufacturing system consisting of a single failure-prone machine and facing constant demands for a number of products. At any given time the system can only produce one type of product, and the system requires a setup if production is to be switched from one type of product to another. A setup may involve setup time or setup cost or both. The objective of the problem is to minimize the total costs of setup, production, and surplus. The control variables are a sequence of setups and a production plan. An asymptotic analysis with respect to increasing rates of change in machine states gives rise to a deterministic limiting optimal control problem in which there is a control variable associated with each of the machine states and the production rate is obtained by weighting these controls with the stationary probabilities of the corresponding states. Asymptotic optimal controls for the original problem from optimal or near-optimal controls for the limiting problem are constructed View full abstract»

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  • Polyspectral and cyclostationary approaches for identification of closed-loop systems

    Page(s): 882 - 885
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    Conventional spectral analysis fails in identifying systems operating with feedback from noisy input-output data. It is shown that polyspectral and cyclic methods can identify closed-loop systems with data corrupted by a class of stationary and cyclostationary noise. The class is specified and nonparametric transfer function estimators are developed and simulated View full abstract»

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  • A tracking controller for flexible joint robots using only link position feedback

    Page(s): 885 - 890
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (476 KB)  

    A dynamic output feedback controller for flexible joint robots is presented which guarantees asymptotic tracking of a desired trajectory, starting from arbitrary initial conditions. The controller needs only the measurements of the positions of the links and the knowledge of an upper bound on the initial tracking error View full abstract»

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  • Continuous-time tracking problems in an H setting: a game theory approach

    Page(s): 841 - 852
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1028 KB)  

    This paper investigates the problem of finite-horizon H tracking for linear time-varying systems. Three tracking problems are considered, depending on whether the reference signal is perfectly known in advance, measured on-line, or previewed in fixed interval of time ahead. No a priori knowledge of a dynamic model for the reference signal is assumed. A game theory approach to the latter tracking problems is presented where, given a specific reference signal, the controllers play against nature which can choose any initial state and any bounded energy disturbance input and measurement noise. Necessary and sufficient conditions for the existence of a saddle-point equilibrium are determined, and H tracking controllers for both the cases of state and output feedback are derived. Tracking problems for time-invariant systems on infinite-horizon are also analyzed, and time invariant tracking controllers are obtained for zero initial conditions 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