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research-article

Design of Complex Engineered System Using Multiagent Coordination

[+] Author and Article Information
Nicolas Soria

School of Mechanical, Industrial and Manufacturing Engineering Oregon State University Corvallis, Oregon, 97331Colegio de Ciencias e Ingeniería Universidad San Francisco de Quito Quito, Ecuador
soriazun@oregonstate.edu

Mitchell K Colby

School of Mechanical, Industrial and Manufacturing Engineering Oregon State University Corvallis, Oregon, 97331
colbym@engr.orst.edu

Irem Y. Tumer

School of Mechanical, Industrial and Manufacturing Engineering Oregon State University Corvallis, Oregon, 97331
irem.tumer@oregonstate.edu

Christopher Hoyle

School of Mechanical, Industrial and Manufacturing Engineering Oregon State University Corvallis, Oregon, 97331
chris.hoyle@oregonstate.edu

Kagan Tumer

School of Mechanical, Industrial and Manufacturing Engineering Oregon State University Corvallis, Oregon, 97331
kagan.tumer@oregonstate.edu

1Corresponding author.

ASME doi:10.1115/1.4038158 History: Received October 05, 2016; Revised October 02, 2017

Abstract

In complex engineering systems, complexity may arise by design, or as a by-product of the system’s operation. In either case, the root cause of complexity is the same: the unpredictable manner in which interactions among components modify system behavior. Traditionally, two different approaches are used to handle such complexity: (i) a centralized design approach where the impacts of all potential system states and behaviors resulting from design decisions must be accurately modeled; and (ii) an approach based on externally legislating design decisions, which avoid such difficulties, but at the cost of expensive external mechanisms to determine trade-offs among competing design decisions. Our approach is a hybrid of the two approaches, providing a method in which decisions can be reconciled without the need for either detailed interaction models or external mechanisms. A key insight of this approach is that complex system design, undertaken with respect to a variety of design objectives, is fundamentally similar to the multiagent coordination problem, where component decisions and their interactions lead to global behavior. The results of this paper demonstrate that a team of autonomous agents using a cooperative coevolutionary algorithm can effectively design a complex engineered system. This publication utilized a system model of a Formula SAE racing vehicle to illustrate and simulate the methods and potential results.

Copyright (c) 2017 by ASME
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