Showing papers in "Automatica in 1985"

TL;DR: This paper presents various theoretical and computational methods for estimating the domain of attraction of an autonomous nonlinear system based on the concept of a maximal Lyapunov function, which is introduced in this paper.

TL;DR: A survey of the field of optimal sensors and/or controllers location for dynamical distributed parameter systems modelled by partial differential equations is presented and a classification of methods is proposed.

TL;DR: Theoretical explanation, backed up by simulations, is offered for the phenomenon of bursts of oscillatory behaviour in the presence of excitations which are not persistently exciting.

TL;DR: This work investigates how an error that is introduced at an arbitrary point in the algorithm propagates and it is shown that conventional LS algorithms are exponentially stable with respect to such errors, i.e. the effect of the error decays exponentially.

TL;DR: It is shown that every strongly stabilizable plant can be reliably stabilized; moreover, one of the two controllers can be specified arbitrarily, subject only to the constraint that it should be stable.

TL;DR: This paper attempts to give a unified overview of how direct methods solve the transient stability problem of large-scale power systems by focusing on the derivation of stability indices, intended for on-line monitoring, contingency evaluation and security control.

TL;DR: The classical model of decision-making under uncertainty is extended to the case when the consequences of a decision are only roughly described and their probabilities of occurrence modeled by intervals or fuzzy numbers.

TL;DR: Simulations and experimental results for an air-conditioning pilot plant show that a considerable improvement of the overall control behaviour can be achieved.

TL;DR: Existence of an optimal controller is proved and a formula for the minimum cost is derived and it is shown that for time-invariant systems an optimal time-varying controller is no better than an optimalTime-Invariant controller.

TL;DR: The classical methods of frequency and spectral analysis are shown to be related to the well-known time domain methods of prediction error type via a common ''empirical transfer function estimate,'' and frequency domain weighting function determines the distribution of bias in case the true system cannot be exactly described within the chosen model set.

TL;DR: The paper considers the task of identifying a causal linear dynamic system excited by stationary Gaussian zero mean noise of unknown spectrum, and given measurements of the system input and output contaminated by independent additive stationary noise signals of unknown spectra.

TL;DR: This work discusses how objective functions can be minimized on-line, thus providing adaptive control, and shows that the self-tuning regulator is obtained as a special case, corresponding to a particular quadratic criterion and a particular way of estimating the system dynamics.

TL;DR: An algorithm is presented for the spectral factorization of polynomial (or rational) matrices arising in optimal control and filtering theory as well as in network theory that is based on Newton's method.

TL;DR: In this article, the authors treat the close conceptual relationships between basic approaches to the estimation of transfer functions of linear systems and show that the classical methods of frequency and spectral analysis are related to the well-known time domain methods of prediction error type via a common empirical transfer function estimate.

TL;DR: The adaptive control of interconnected systems whose subsystems possess slow and fast modes is investigated in the presence of external disturbances and an approach is developed for stabilization and tracking using decentralized adaptive controllers with modified adaptive laws.

TL;DR: It is shown that the adaptive closed loop control system can be written as an exponentially stable system driven by the identification error.

TL;DR: This brief overview discusses four recent approaches: linear robust multivariable control, adaptive control, nonlinear composite control and external linearization design.

TL;DR: The mean square tracking deviation (MSD) between the optimum vector and the algorithm output is proved to include two contributions; the stationary mode error, characteristic of convergence accuracy, which is proportional to the step-size; and the transient modeerror, reflecting the rapidity of tracking,Which agrees with the common intuition that there exists an optimum step- size which compromises between convergence accuracy and tracking speed.

TL;DR: An LQG synthesis algorithm is presented that optimizes the parameters of a multi-input, multi-output compensator for a linear time-invariant plant, where the designer specifies the order and the structure of the compensator.

TL;DR: An adaptive regulator which uses the a priori known information and satisfies the multi-objective character of the control is presented which eliminates the effect of the area load fluctuations to the tie-line power and guarantees the scheduled value of the exported/imported energy.

TL;DR: This report presents ways to meet the requirements of inferential control and applies the methods to an industrial autoclave plant and to a laboratory heat exchange system.

TL;DR: The authors have attempted to give a unified presentation of the various existing schemes by stripping away the technical details and highlighting their close interrelation through the use of a common framework.

TL;DR: The problem to estimate transfer functions of linear systems is considered and how such a prejudice can be reduced by allowing the possibility that the true system cannot be exactly described in the chosen model set is discussed.

TL;DR: By relaxing the observability assumption to detectability, an extended version of the lemma is obtained, where the system stability is linked with the existence of a periodic positive semidefinite solution of the Lyapunov equation.

TL;DR: A convergent version of the Anderson-Moore algorithm for the optimal output feedback problem is applied to a class of optimal decentralized control problems and performs favourably when compared with the method of Geromel and Bernussou (1979) and with variable metric function minimization techniques.

TL;DR: This work investigates the case where the random field is not necessarily stationary, where the data are so scarce and so scattered in space that sample covariance function estimates are not meaningful and where, therefore, an analytical parametric 'variogram' model is used in lieu of the covariance.

TL;DR: Definitions of external behaviour, equivalence and minimality are given for a class of implicit non-oriented linear dynamical systems of particular interest in computer-aided analysis and design.

TL;DR: A robustness test which can be used to assess closed-loop stability when the nominal plant model and perturbed plant model have different numbers of poles and zeros in the right-half plane is presented.