228 research outputs found

    Handling Clone Mutations in Simulink Models with VCL

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    Like any other software system, real life Simulink models contain a considerable amount of cloning. These clones are not always identical copies of each other, but actually show a variety of differences from each other despite the overall similarities. Insufficient variability mechanisms provided by the platform make it difficult to create generic structures to represent these clones. Also, complete elimination of clones from the systems may not always be practical, feasible, or cost-effective. In this paper we propose a mechanism for clone management based on Variant Configuration Language (VCL) that provides a powerful variability handling mechanism. In this mechanism, the clones will be managed separate from the models in a non-intrusive way and the original models will not be polluted with extra complexity to manage clone instances. The proposed technique is validated by creating generic solutions for Simulink clones with a variety of differences present between them

    Model analytics and management

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    Model analytics and management

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    Prescription of rhythmic patterns for legged locomotion

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    As the engine behind many life phenomena, motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree-of-freedom (DOF) with adjustable oscillatory frequencies and duty cycles. An OBBs network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration
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