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dc.contributor.authorWiechula, Stefan
dc.date.accessioned2007-03-07 15:43:05 (GMT)
dc.date.available2007-03-07 15:43:05 (GMT)
dc.date.issued2007-03-07T15:43:05Z
dc.date.submitted2006
dc.identifier.urihttp://hdl.handle.net/10012/2739
dc.description.abstractThe contributions of this work include genetic programming grammars for bond graph modelling and for direct symbolic regression of sets of differential equations; a bond graph modelling library suitable for programmatic use; a symbolic algebra library specialized to this use and capable of, among other things, breaking algebraic loops in equation sets extracted from linear bond graph models. Several non-linear multi-body mechanics examples are pre- sented, showing that the bond graph modelling library exhibits well-behaved simulation results. Symbolic equations in a reduced form are produced au- tomatically from bond graph models. The genetic programming system is tested against a static non-linear function identification problem using type- less symbolic regression. The direct symbolic regression grammar is shown to have a non-deceptive fitness landscape: perturbations of an exact pro- gram have decreasing fitness with increasing distance from the ideal. The planned integration of bond graphs with genetic programming for use as a system identification technique was not successfully completed. A catego- rized overview of other modelling and identification techniques is included as context for the choice of bond graphs and genetic programming.en
dc.format.extent4448967 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.titleTools for Modelling and Identification with Bond Graphs and Genetic Programmingen
dc.typeMaster Thesisen
dc.pendingfalseen
dc.subject.programMechanical Engineeringen
uws-etd.degree.departmentMechanical and Mechatronics Engineeringen
uws-etd.degreeMaster of Applied Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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