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Abstract The aim of this work is to propose a methodology of sizing in a frame of the conception of mechatronic systems in particular and active dynamic ones, in general. This methodology will support conceptual design step [1]. We propose a collaborative design approach based on Bond Graph tool and Genetic algorithms. Mechatronic systems have a passive part and active part. In our approach we establish a hard interaction between passive and active parts. This interaction will be materialized in taking into account of control criteria in the evolution (synthesis) phase of passive part. This initiative treats functional aspects, both structural and behavioral; while respecting interactions between passive and active parts. In our approach we treat functional, structural and behavioral aspects in order to validate a post-project solution. Optimization needs Behavioral models which are systematically deducted from bond-graph structural models. Thus, retained bond graph elements which constitute passive part will be obtained, done by optimization Genetic Algorithms procedure. In this procedure Gramians of controllability and of observability represent the fitness function. The proposed method will be applied to an automatic transmission of a scooter and validated by a dynamic simulation. Keywords: Modeling, dynamic system, Bond graph, Gramians of controllability, Genetic algorithms
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andrea1902
Abstract The aim of this work is to propose a methodology of sizing in a frame of the conception of mechatronic systems in particular and active dynamic ones, in general. This methodology will support conceptual design step [1]. We propose a collaborative design approach based on Bond Graph tool and Genetic algorithms. Mechatronic systems have a passive part and active part. In our approach we establish a hard interaction between passive and active parts. This interaction will be materialized in taking into account of control criteria in the evolution (synthesis) phase of passive part. This initiative treats functional aspects, both structural and behavioral; while respecting interactions between passive and active parts. In our approach we treat functional, structural and behavioral aspects in order to validate a post-project solution. Optimization needs Behavioral models which are systematically deducted from bond-graph structural models. Thus, retained bond graph elements which constitute passive part will be obtained, done by optimization Genetic Algorithms procedure. In this procedure Gramians of controllability and of observability represent the fitness function. The proposed method will be applied to an automatic transmission of a scooter and validated by a dynamic simulation. Keywords: Modeling, dynamic system, Bond graph, Gramians of controllability, Genetic algorithms
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