Showing papers in "Automatica in 1980"

TL;DR: The basic ideas behind the parameter estimation methods are discussed in a general setting and an example is given which illustrates some properties of the methods and shows the usefulness of interactive computing.

TL;DR: In this paper some human dynamic properties are outlined to illustrate the variety of human behavior, and some suitable theoretical treatments are summarized.

TL;DR: A multivariable self-tuning controller is derived extending the scalar version of Clarke and Gawthrop (1975) because the control terms are penalized in the cost function, fluctuations and peaking in control signals are reduced.

TL;DR: It is concluded that an experimental fuzzy control algorithm constructed to reflect actual operational practice does rather well and that a fuzzy controller would be a useful and practical way of regulating the activated sludge process.

TL;DR: In the paper some robust estimators for nonlinear regression problems are proposed and their features are discussed.

TL;DR: The paper describes a simple instrumental variable method for identifying the structure of a wide class of time-series models that can be applied to single input-single output and multivariable systems using either discrete or continuous-time series models.

TL;DR: This tutorial paper presents an iterative method for the separation of slow and fast modes, which removes the inconsistencies of the classical quasi-steady-state approach and systematically improves the accuracy of the lower order models.

TL;DR: The new approach to shown to handle both nonsquare and/or degenerate systems without difficulties whereas earlier methods would either fail or would require special treatment fo r these cases.

TL;DR: In this tutorial very simple methods will be presented by which models for dynamic processes can be obtained that employ step responses of the process or responses to other nonperiodic testsignals or process responses to periodic signals.

TL;DR: The theory of correlation methods is discussed, emphasising the use of crosscorrelation to determine weighting functions of linear systems and the corresponding frequency domain expressions are derived.

TL;DR: A method for constructing a multivariable P-controller, which uses interactions of the plant, is developed, which is also based on step-responses.

TL;DR: This article demonstrates the application of least squares for the estimation of system parameters and solutions are discussed for the case of white noise and correlated noise corrupting the useful output signal of the system.

TL;DR: A general procedure of process identification, the selection of input signals, theselection of the sampling time, off-line and on-line identification, comparison of parameter estimation methods, model order testing and model verification is presented.

TL;DR: A grouping algorithm is proposed which reduces the area decomposition problem to obtaining a basis for the slow subsystem and performing a Gaussian elimination.

TL;DR: The derivation of closed-loop Stackelberg (CLS) solutions of a class of continuous-time two-player nonzero-sum differential games characterized by linear state dynamics and quadratic cost functionals is concerned.

TL;DR: Several recurisve algorithms for parametric identification of discrete time systems derived from Model Reference Adaptive System (M.R.A.S.) techniques are analysed, belonging to the class of output error methods which have been very little discussed previously in the identification literature.

TL;DR: Assembly research comprises the definitive description of how parts interact during assembly, the collection of part mating processes into systems that assemble products, and the integration of this process into the factory as a whole.

TL;DR: Adaptive control algorithms may be applied for adaptive control of constant and time variant, linear and weakly non-linear stable and unstable processes with process computers or micro computers or for self-tuning of control algorithms or tuning of conventional analog PID controllers.

TL;DR: Linear simulation results in two- and four-time-scales demonstrate the potential applicability of the singular perturbation approach to long-term dynamic studies of power systems.

TL;DR: A class of large-scale systems is defined, which can always be stabilized by local feedback, and Stability of the closed-loop system is connective and can tolerate nonlinearities in the interconnections.

TL;DR: It is shown that a discrete time integrating regulator can be designed based on a strongly simplified model which has only two tuning parameters which are easy to choose from the step response of the open loop system.

TL;DR: In this article, the concept of decomposition is applied to the control synthesis of multivariable mechanical systems, in which the coupling among the subsystems can be very strong, and global control is introduced to diminish the influence of coupling on the stability of the whole system.

TL;DR: Stabilizability subspaces are introduced, are given a frequency domain characterization and are used to solve design problems.

TL;DR: A model of the heart rate regulation during physical load and recovery has been developed and is useful practically for the evaluation of the physical efficiency of individuals and whole groups of healthy subjects.

TL;DR: The problem is studied of estimating the arrival times and heights of pulses of known shape observed with white additive noise, and an estimation algorithm is described, and its consistency is proved.

TL;DR: The problem of daily controlling a water distribution network, including pumping devices and storage capacities, in order to supply the consumers at the lowest cost is formulated as a constrained optimal control problem.

TL;DR: For stochastically observable, linear systems explicit expressions for the LUMCE of the state at time t@?0, with no information of the initial state, are obtained.

TL;DR: The purpose of this paper is to clarify the relations and to provide some selection guides among several time-series identification algorithms that appear in the literature under different names but which are essentially least-squares identification algorithms where only the numerical solution of the least-Squares estimation problem is different.

TL;DR: This report presents a method for obtaining low order models of high order stable linear systems which match the frequency response of the high order system at a set of prespecified frequencies.

TL;DR: It was found that through the nonstationary noise model and the optimal sensor location significantly improved state estimates can be obtained when persistent or slowly varying unmeasured disturbances affect the system.