Doctoral Dissertations

Abstract

"The effects of input delay on an identification scheme using a learning model are investigated. The parameter adjustment laws for the learning model are derived through Lyapunov methods similar to those used for the model reference adaptive control systems of Parks. For no measurement noise or delay mismatch between the learning model and system, the parameters are adjusted to bring the error between model and plant to zero. When there is delay mismatch between the inputs of the learning model and the unknown system, the convergence of the parameters of the learning model to those of the unknown system is no longer guaranteed. However, the error between the learning model and the unknown system is guaranteed to enter and stay within a region close to the origin. Several methods of reducing the region are investigated. These methods involve deriving additional adaptive laws for controlling an adjustable delay in the learning model. Asymptotic stability is assured when the initial parameter misalignment vector lies in some region close to the origin. The identification schemes are demonstrated with examples"--Abstract, pages x-xi.

Advisor(s)

Pazdera, John S., 1941-1974

Committee Member(s)

Noack, Thomas L.
Kern, Frank J.
Rivers, Jack L.
Tracey, James H.

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

1971

Pagination

xi, 104 pages

Note about bibliography

Includes bibliographical references.

Rights

© 1971 Hugh Francis Spence, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Linear control systems
Linear systems
Adaptive control systems

Thesis Number

T 2625

Print OCLC #

6038809

Electronic OCLC #

878044546

Share

 
COinS