Cooperative body-brain coevolutionary synthesis of mechatronic systems

Jiachuan Wang, Zhun Fan, Janis P. Terpenny, Erik D. Goodman

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

To support the concurrent design processes of mechatronic subsystems, unified mechatronics modeling and cooperative body-brain coevolutionary synthesis are developed. In this paper, both body-passive physical systems and brain-active control systems can be represented using the bond graph paradigm. Bond graphs are combined with genetic programming to evolve low-level building blocks into systems with high-level functionalities including both topological configurations and parameter settings. Design spaces of coadapted mechatronic subsystems are automatically explored in parallel for overall design optimality. A quarter-car suspension system case study is provided. Compared with conventional design methods, semiactive suspension designs with more creativity and flexibility are achieved through this approach.

Original languageEnglish (US)
Pages (from-to)219-234
Number of pages16
JournalArtificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Volume22
Issue number3
DOIs
StatePublished - Aug 1 2008

Fingerprint

Mechatronics
Brain
Genetic programming
Railroad cars
Control systems

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

Cite this

Wang, Jiachuan ; Fan, Zhun ; Terpenny, Janis P. ; Goodman, Erik D. / Cooperative body-brain coevolutionary synthesis of mechatronic systems. In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM. 2008 ; Vol. 22, No. 3. pp. 219-234.
@article{40d70a8c64354a5d9d2b1e655bb5d9b3,
title = "Cooperative body-brain coevolutionary synthesis of mechatronic systems",
abstract = "To support the concurrent design processes of mechatronic subsystems, unified mechatronics modeling and cooperative body-brain coevolutionary synthesis are developed. In this paper, both body-passive physical systems and brain-active control systems can be represented using the bond graph paradigm. Bond graphs are combined with genetic programming to evolve low-level building blocks into systems with high-level functionalities including both topological configurations and parameter settings. Design spaces of coadapted mechatronic subsystems are automatically explored in parallel for overall design optimality. A quarter-car suspension system case study is provided. Compared with conventional design methods, semiactive suspension designs with more creativity and flexibility are achieved through this approach.",
author = "Jiachuan Wang and Zhun Fan and Terpenny, {Janis P.} and Goodman, {Erik D.}",
year = "2008",
month = "8",
day = "1",
doi = "10.1017/S0890060408000152",
language = "English (US)",
volume = "22",
pages = "219--234",
journal = "Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM",
issn = "0890-0604",
publisher = "Cambridge University Press",
number = "3",

}

Cooperative body-brain coevolutionary synthesis of mechatronic systems. / Wang, Jiachuan; Fan, Zhun; Terpenny, Janis P.; Goodman, Erik D.

In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, Vol. 22, No. 3, 01.08.2008, p. 219-234.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Cooperative body-brain coevolutionary synthesis of mechatronic systems

AU - Wang, Jiachuan

AU - Fan, Zhun

AU - Terpenny, Janis P.

AU - Goodman, Erik D.

PY - 2008/8/1

Y1 - 2008/8/1

N2 - To support the concurrent design processes of mechatronic subsystems, unified mechatronics modeling and cooperative body-brain coevolutionary synthesis are developed. In this paper, both body-passive physical systems and brain-active control systems can be represented using the bond graph paradigm. Bond graphs are combined with genetic programming to evolve low-level building blocks into systems with high-level functionalities including both topological configurations and parameter settings. Design spaces of coadapted mechatronic subsystems are automatically explored in parallel for overall design optimality. A quarter-car suspension system case study is provided. Compared with conventional design methods, semiactive suspension designs with more creativity and flexibility are achieved through this approach.

AB - To support the concurrent design processes of mechatronic subsystems, unified mechatronics modeling and cooperative body-brain coevolutionary synthesis are developed. In this paper, both body-passive physical systems and brain-active control systems can be represented using the bond graph paradigm. Bond graphs are combined with genetic programming to evolve low-level building blocks into systems with high-level functionalities including both topological configurations and parameter settings. Design spaces of coadapted mechatronic subsystems are automatically explored in parallel for overall design optimality. A quarter-car suspension system case study is provided. Compared with conventional design methods, semiactive suspension designs with more creativity and flexibility are achieved through this approach.

UR - http://www.scopus.com/inward/record.url?scp=45749140480&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=45749140480&partnerID=8YFLogxK

U2 - 10.1017/S0890060408000152

DO - 10.1017/S0890060408000152

M3 - Article

VL - 22

SP - 219

EP - 234

JO - Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

JF - Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

SN - 0890-0604

IS - 3

ER -