On the theory of self-adjusting models

doi:10.1016/0005-1098(63)90014-1

Automatica

Volume 1, Issue 4, December 1963, Pages 297-309

https://doi.org/10.1016/0005-1098(63)90014-1 Get rights and content

Abstract

A method of obtaining the self-adjusting action in nonstationary linear models has been derived. A stability theorem establishing the local asymptotic stability of the self-adjusting mechanism in quasi stationary tracking has been proved.

Résumé

Une méthode pour obtenir l'action d'auto-réglage dans les modèles linéaires non-station-aires est développée. Un théoreme de stabilité établissant la stabilité asymptatique locale du mécanisme d'auto-réglage en poursuite quasi-stationaire est démontré.

Zusammenfassung

Hergeleitet wurde eine Methode, mit der man in nichtstationären linearen Modellen einen selbsteinstellenden Prozess ermittelt. Ein Stabilitätstheorem, das die lokale asymptotische Stabilität der selbsteinstellenden Erinrichtung im quasistationären Suchprozess begründet, wurde geprüft.

Реферат

Paзвит мeтoд пoлyчeния caмoyпpaвляющeгocя дeйcтвия в линeйныч нecтaциoнapныч мoдeляч. Дoкaзaнa тeopeмa ycтoйчивocти oпpeдeляющaя мecтнyю acимитoтичecкyю ycтoйчивocть мeчaнизмa caмoyпpaвлeния в квaзиcтaциoнapнoм cлeфeнии.

References (11)

A.A. Krasovski
The first IFAC congress publications, part 2
V.N. Varygin
Certain Problems in Designing Systems with Extremal Self-Adjusting Corrective Devices
(August, 1961)
N.V. Grishko
The Determination of Optimal Characteristics for an Extremal System with Random Disturbances
(February, 1962)
I.E. Kazakov
The Dynamics of Self-Adaptive Systems with Extremal Continuous Adjustments of the Compensating Network in the Presence of Random Disturbances
(May 1961)
M. Margolis et al.
The first IFAC congress publications, part 2

There are more references available in the full text version of this article.

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This chapter describes control. The basic principle underlying the design of automatic control systems is the principle of control by error signals or the principle of negative feedback. If an error signal reflects different uncontrollable external actions (disturbances), then it can serve as a measure of deviation of the system from a prescribed regime for which such an error signal would not exist. Insufficient a priori information necessitates a certain combination of plant identification and control. We cannot control a plant in an optimal fashion without knowing its characteristics, but we can study a plant by controlling it. This can then give us an opportunity to improve the control and eventually to reach an optimal control law. In dual control systems there is always a conflict between the identification and the control aspects of a control action. Successful control is possible if the properties of a plant are well-known and the controller can quickly react to the variations in the state of the plant. One can construct the sensitivity models for nonlinear plants.
Three Knowledge Sources and Three Constituents of Artificial Intelligence Foundation
2023, Lecture Notes in Networks and Systems

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On the theory of self-adjusting models

Abstract

Résumé

Zusammenfassung

Реферат

The first IFAC congress publications, part 2

Certain Problems in Designing Systems with Extremal Self-Adjusting Corrective Devices

The Determination of Optimal Characteristics for an Extremal System with Random Disturbances

The Dynamics of Self-Adaptive Systems with Extremal Continuous Adjustments of the Compensating Network in the Presence of Random Disturbances

The first IFAC congress publications, part 2