Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1947
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dc.contributor.authorSamarakoon, B. L-
dc.contributor.authorGamage, L. B-
dc.contributor.authorde Silva, C. W-
dc.date.accessioned2022-04-08T07:41:28Z-
dc.date.available2022-04-08T07:41:28Z-
dc.date.issued2016-02-01-
dc.identifier.issn0957-4158 .-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1947-
dc.description.abstractThis paper presents a scheme of evolutionary design optimization, which integrates modeling with bond graphs and optimization using genetic programming for multi-domain engineering systems, particularly mechatronic systems. The performance of the developed system is studied using both experimentation and simulation. During the evolutionary optimization, in addition to the desired response error, system complexity is also taken into account. For the experimental study, the method is implemented in an industrial fish processing machine at the Industrial Automation Laboratory of the University of British Columbia, and the obtained results for suggested design modifications are studied and tested. The drawbacks of the fitness calculation methodologies that are presented in literature are identified and improved fitness functions are developed for evolutionary design in the present work. While previous work has investigated the integration of bond graphs and genetic programming for designing an engineering system, the present work specifically addresses the application of the developed method for the design improvement of an industrial machine. The proposed method is applicable particularly to existing engineering systems, first because the initial model can be tested by comparing its simulated results with the corresponding results from the actual physical system, and second because the design improvements as suggested by the evolutionary design framework, which is developed in the present work, may be implemented and tested against the behavior of the corresponding model.en_US
dc.language.isoenen_US
dc.publisherPergamonen_US
dc.relation.ispartofseriesMechatronics;Vol 33 Pages 71-83-
dc.subjectGenetic programmingen_US
dc.subjectAutomated design optimizationen_US
dc.subjectModelingen_US
dc.subjectMechatronicsen_US
dc.titleDesign evolution of engineering systems using bond graphs and genetic programmingen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.mechatronics.2015.09.009en_US
Appears in Collections:Research Papers - Department of Electrical and Electronic Engineering
Research Papers - SLIIT Staff Publications

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