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
Subject Headings
Linear control systemsLinear systemsAdaptive control systems
Thesis Number
T 2625
Print OCLC #
6038809
Electronic OCLC #
878044546
Recommended Citation
Spence, Hugh Francis, "Identification of linear systems with delay via a learning model" (1971). Doctoral Dissertations. 1854.
https://scholarsmine.mst.edu/doctoral_dissertations/1854