Doctoral Dissertations

Keywords and Phrases

Fuzzy inference system; System architecting; Systems of systems

Abstract

"This research proposes a domain independent method to build and assess systems of systems (SoS) architecture models. A simplified meta-architecture containing each component system's participation and a first order, binary, system-to-system interface is proposed. The method describes how to elicit desired SoS attributes from stakeholders. Measures of the attributes depend on systems' participation and interfaces, that is, on the SoS architecture. The goal is to model a realizable SoS configuration, optimized over multiple attributes. Key attribute measures are combined in a fuzzy inference system to assess an overall fitness measure for any SoS in the meta-architecture. A genetic algorithm is used to find 'good' SoS architectures with a fitness that depends on the participation framework. This research illustrates a method to define architecture sensitive attributes and build the fuzzy assessor. These are two segments of the Missouri S&T developed nine part Flexible Intelligent Learning Architectures for SoS (FILA-SoS) research approach to architecting SoS. A desirable SoS architecture may be handed off to an agent-based model to examine the impact of various negotiation behaviors or policies on realization of the SoS. The final configuration can evolve over several development epochs in the wave model.

The method is demonstrated on SoS in several domains to illustrate its broad generality. Two intelligence, surveillance and reconnaissance (ISR) SoS, a search and rescue (SAR) SoS, two versions of the MITRE Toy problem, and an actual SoS for a large training program are analyzed. The method provides researchers and designers with a novel way to think about the effects of imprecise stakeholder desires and acquisition policies on SoS architecting"--Abstract, page iii.

Advisor(s)

Dagli, Cihan H., 1949-

Committee Member(s)

Corns, Steven
Guardiola, Ivan
Enke, David Lee, 1965-
Paunicka, James
Ergin, Nil

Department(s)

Engineering Management and Systems Engineering

Degree Name

Ph. D. in Systems Engineering

Sponsor(s)

United States. Department of Defense

Comments

Supported by the United States Department of Defense through the Systems Engineering Research Center (SERC) under Contract H98230-08-D-0171
SERC funded the RT-37, RT-44c and RT-109 research tasks titled “An Advanced Computational Approach To SoS Analysis And Architecting Using Agent-Based Behavioral Modeling.”

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2016

Pagination

xxi, 235, A2, B56, C9, D4, E14 pages

Note about bibliography

Includes bibliographic references (pages 219-232).

Rights

© 2016 Louis Edward Pape II, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Subject Headings

Computer architecture -- Evaluation -- DesignSystems engineering -- Data processing -- DesignEvolutionary programming (Computer science) -- Genetic algorithmsFuzzy systems

Thesis Number

T 10923

Electronic OCLC #

952598150

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