A design methodology for self-tuning control of systems with inherent conflicts
Hung, Stephen Think
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/23584
Description
Title
A design methodology for self-tuning control of systems with inherent conflicts
Author(s)
Hung, Stephen Think
Issue Date
1989
Doctoral Committee Chair(s)
Kokotovic, P.V.
Department of Study
Engineering, Electronics and Electrical
Discipline
Engineering, Electronics and Electrical
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
Outlined in this thesis is a methodology for the design of self-tuning controllers for systems with inherent control conflicts. These conflicts arise from either physical phenomena or user specifications. An intrinsic part of this methodology is the extensive collection and computer-aided incorporation of a priori information in the design process to enable realization of controllers of relatively simple structure and of low on-line computational requirements. Such simple solutions to complex problems are often overlooked when a priori information is unnecessarily neglected in some of the more mathematically elegant self-tuning algorithms proposed to date. Another intrinsic element of the methodology is the use of integral manifold and averaging techniques to simplify the analysis and design of self-tuning control of real processes. This serves not to confuse the design engineer, but to demonstrate the practical nature of some of the control theorist's tools.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.