Towards computer-automated mechatronic design and optimization using linear graphs and evolutionary computing

dc.contributor.advisorLang, Haoxiang
dc.contributor.authorMcCormick, Eric
dc.date.accessioned2020-10-20T19:39:14Z
dc.date.accessioned2022-03-29T19:59:33Z
dc.date.available2020-10-20T19:39:14Z
dc.date.available2022-03-29T19:59:33Z
dc.date.issued2020-04-01
dc.degree.disciplineMechanical Engineeringen
dc.degree.levelMaster of Applied Science (MASc)en
dc.description.abstractA comparison of literature between the linear graph (LG) and bond graph (BG) approaches shows that the surpassing of BGs to LGs in applications related to the modeling of mechatronic systems is driven primarily by a lack of available LG-based software. As a result, a robust software toolbox called LGtheory has been developed for automating the evaluation of LG models in the MATLAB programming environment. This thesis details the development of LGtheory, and the algorithms and procedures employed for the evaluation of LG models. In addition, demonstrations of this toolbox to a process for automating the design of electronic filter circuits, as well as, the modeling and simulation of the dynamics of a mobile robotic system are presented. The results of these demonstrations validate the accuracy of the LGtheory toolbox for modeling complex multi-domain systems, and provides the methodological basis for the automated design of mechatronic systems using LGs.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.identifier.urihttps://hdl.handle.net/10155/1171
dc.language.isoenen
dc.subjectLinear Graph Modelingen
dc.subjectMechatronicsen
dc.subjectAutomated Designen
dc.subjectGenetic Programmingen
dc.subjectGenetic Algorithmsen
dc.titleTowards computer-automated mechatronic design and optimization using linear graphs and evolutionary computingen
dc.typeThesisen

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