Abstract/Details

Domain adaptive control architecture for advanced manufacturing systems


2006 2006

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Abstract (summary)

The main objective of this study is to design, develop, and investigate domain adaptive control architecture for advanced manufacturing systems. The proposed control architecture is a swarm-based, multi-agent system that exhibits adaptive and emergent behavior that has been inspired from social insects, such as wasps.

The proposed control architecture is built on a decentralized model, which does not require any user-defined control parameters but rather employs stigmergic communication that results in emerging behavior with minimal negotiation overhead. Inspired from natural systems, the architecture is based on simple rules that self-adapts automatically based on the real-time status of the manufacturing system. A 3-layer modular software platform that includes MATLAB ® codes, ARENA® simulation models, Visual Basic ® modules, and MS ACCESS® database, is developed to facilitate experimentation and benchmarking.

The proposed control architecture is applied to a variety of manufacturing domains and benchmarked against studies from the literature. A variety of experiments, involving internal and external dynamic disturbances, is performed. The experimental results clearly show that the proposed model is more reliable, adaptable, scalable, survivable, and robust and outperforms all the benchmarked models and heuristics. This research adds to the literature the advantages of applying stigmergy as a means of communication among agents in a multi-agent system. The research clearly shows as how the mathematical model developed for wasp life-cycle can be directly mapped and used to proactively control manufacturing systems.

Indexing (details)


Subject
Industrial engineering;
Artificial intelligence
Classification
0546: Industrial engineering
0800: Artificial intelligence
Identifier / keyword
Applied sciences; Agent-based; Manufacturing; Swarm intelligence
Title
Domain adaptive control architecture for advanced manufacturing systems
Author
Meyyappan, Lakshmanan
Number of pages
104
Publication year
2006
Degree date
2006
School code
0135
Source
DAI-B 68/01, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
Advisor
Dagli, Cihan H.; Saygin, Can
University/institution
University of Missouri - Rolla
University location
United States -- Missouri
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3248205
ProQuest document ID
305262995
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/305262995
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