A cell-to-cell mapping based analysis and design of fuzzy dynamic systems and its applications

Persistent Link:
http://hdl.handle.net/10150/282096
Title:
A cell-to-cell mapping based analysis and design of fuzzy dynamic systems and its applications
Author:
Pu, Bing, 1966-
Issue Date:
1995
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Systematic design and analysis of fuzzy dynamic systems has been a problem which attracted much attention from researchers in recent years. In this dissertation, we propose a methodology for analysis and design of fuzzy dynamic systems. First, we introduce a new way to treat fuzzy sets: fuzzy sets as points in fuzzy state space. We investigate the relationship between membership functions and their corresponding fuzzy set points in fuzzy state space. We then examine the formulation and stability issues of fuzzy dynamic systems based on the geometric structure of fuzzy state space, resulting in the generalization and extension of classical stability definitions to fuzzy dynamic systems. We also introduce cellular structure to fuzzy state space, allowing a discrete cell-to-cell mapping method to be developed to approximate a fuzzy dynamic system model. This method leads to an efficient global behavior analysis algorithm based on a simple cell-to-cell mapping search. Finally, we outline the cellmapping-based search algorithm for fuzzy optimal control design and demonstrate its validity and advantages by applying it to time-optimal trajectory generation for coordinated manipulator systems with uncertain parameters.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Engineering, Electronics and Electrical.; Engineering, Industrial.; Engineering, System Science.; Artificial Intelligence.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Systems and Industrial Engineering
Degree Grantor:
University of Arizona
Advisor:
Wang, Fei-Yue

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleA cell-to-cell mapping based analysis and design of fuzzy dynamic systems and its applicationsen_US
dc.creatorPu, Bing, 1966-en_US
dc.contributor.authorPu, Bing, 1966-en_US
dc.date.issued1995en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractSystematic design and analysis of fuzzy dynamic systems has been a problem which attracted much attention from researchers in recent years. In this dissertation, we propose a methodology for analysis and design of fuzzy dynamic systems. First, we introduce a new way to treat fuzzy sets: fuzzy sets as points in fuzzy state space. We investigate the relationship between membership functions and their corresponding fuzzy set points in fuzzy state space. We then examine the formulation and stability issues of fuzzy dynamic systems based on the geometric structure of fuzzy state space, resulting in the generalization and extension of classical stability definitions to fuzzy dynamic systems. We also introduce cellular structure to fuzzy state space, allowing a discrete cell-to-cell mapping method to be developed to approximate a fuzzy dynamic system model. This method leads to an efficient global behavior analysis algorithm based on a simple cell-to-cell mapping search. Finally, we outline the cellmapping-based search algorithm for fuzzy optimal control design and demonstrate its validity and advantages by applying it to time-optimal trajectory generation for coordinated manipulator systems with uncertain parameters.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectEngineering, Industrial.en_US
dc.subjectEngineering, System Science.en_US
dc.subjectArtificial Intelligence.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSystems and Industrial Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorWang, Fei-Yueen_US
dc.identifier.proquest9603724en_US
dc.identifier.bibrecord.b33521013en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.