TY - GEN
T1 - Bond graph modeling and simulation of mechatronic systems
AU - Malik, M. A.
AU - Khurshid, A.
N1 - Publisher Copyright:
© 2003 IEEE.
PY - 2003
Y1 - 2003
N2 - The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only. Mechatronic systems, being a mix of mechanical and electronic systems, deal with multi-domain systems. Such systems may typically include translational, rotational, thermofluid, electrical, electromechanical and electronic systems. Modeling and simulation of such multi-domain systems pose formidable new challenges and, hence, demand new strategies and techniques for reliable solutions. The bond graph method (BGM) is rapidly emerging to offer a new modeling and simulation methodology that is ideally suited to effectively unify knowledge pertaining to multi-domain systems for mechatronic applications. The BGM combined with genetic programming (GP) offers tremendous opportunities in artificial intelligence, image processing, and robotic and industrial automation, The extension of BGM for applications to fields such as social behavior, economics and operational research is a very active topic of current research. This work illustrates the methodology offered by BGM for modeling and simulation of mechatronic systems.
AB - The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only. Mechatronic systems, being a mix of mechanical and electronic systems, deal with multi-domain systems. Such systems may typically include translational, rotational, thermofluid, electrical, electromechanical and electronic systems. Modeling and simulation of such multi-domain systems pose formidable new challenges and, hence, demand new strategies and techniques for reliable solutions. The bond graph method (BGM) is rapidly emerging to offer a new modeling and simulation methodology that is ideally suited to effectively unify knowledge pertaining to multi-domain systems for mechatronic applications. The BGM combined with genetic programming (GP) offers tremendous opportunities in artificial intelligence, image processing, and robotic and industrial automation, The extension of BGM for applications to fields such as social behavior, economics and operational research is a very active topic of current research. This work illustrates the methodology offered by BGM for modeling and simulation of mechatronic systems.
KW - Bonding
KW - Circuits
KW - Computational modeling
KW - Decision making
KW - Flow graphs
KW - Genetics
KW - Humans
KW - Mechatronics
KW - Predictive models
KW - Robotics and automation
UR - http://www.scopus.com/inward/record.url?scp=84948187120&partnerID=8YFLogxK
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U2 - 10.1109/INMIC.2003.1416738
DO - 10.1109/INMIC.2003.1416738
M3 - Conference contribution
AN - SCOPUS:84948187120
T3 - Proceedings - INMIC 2003: IEEE 7th International Multi Topic Conference
SP - 309
EP - 314
BT - Proceedings - INMIC 2003
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Multi Topic Conference, INMIC 2003
Y2 - 8 December 2003 through 9 December 2003
ER -