An Analog Neural Net Based Suboptimal Controller For Constrained Discrete-Time Linear-Systems

    Authors

    M. Sznaier;M. J. Damborg

    Comments

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    Abbreviated Journal Title

    Automatica

    Keywords

    Analog Computer Control; Discrete-Time Systems; Feedback Control; Multivariable Control Systems; Neural Nets; Online Operations; Stability; Suboptimal Control; Networks; Automation & Control Systems; Engineering, Electrical & Electronic

    Abstract

    A large class of problems frequently encountered in practice involves the control of linear time invariant systems with states and controls restricted to closed convex regions of their respective spaces. In spite of the significance of this problem, to date it has not been solved satisfactorily except in some restricted cases. In this paper we propose a suboptimal feedback control algorithm based upon on-line optimization during the sampling interval. Theoretical results are presented showing that our approach yields asymptotically stable systems. Finally an implementation of the control algorithm using an analog circuit is discussed. This implementation provides an alternative to the use of digital computers in the feedback loop that offers advantages in terms of cost and reliability. We believe that it may prove to be specially valuable when the time available for computations is limited. A 5th-order model of a F-100 jet engine is used as an example application of the controller.

    Journal Title

    Automatica

    Volume

    28

    Issue/Number

    1

    Publication Date

    1-1-1992

    Document Type

    Note

    Language

    English

    First Page

    139

    Last Page

    144

    WOS Identifier

    WOS:A1992HB05300012

    ISSN

    0005-1098

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