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Advances in space mapping technology exploiting implicit space mapping and output space mapping

Posted on:2005-08-21Degree:Ph.DType:Thesis
University:McMaster University (Canada)Candidate:Cheng, QingshaFull Text:PDF
GTID:2450390011951099Subject:Engineering
Abstract/Summary:
This thesis contributes to advances in Space Mapping (SM) technology in computer-aided modeling, design and optimization of engineering components and devices. Our developments in modeling and optimization of microwave circuits include the SM framework and SM-based surrogate modeling; implicit SM optimization exploiting preassigned parameters; implicit, frequency and output SM surrogate modeling and design; an SM design framework and implementation techniques.; We review the state of the art in space mapping and the SM-based surrogate (modeling) concept and applications. In the review, we recall proposed SM-based optimization approaches including the original algorithm, the Broyden-based aggressive SM algorithm, various trust region approaches, neural space mapping and implicit space mapping. Parameter extraction (PE) is developed as an essential SM subproblem. Different approaches to enhance uniqueness of PE are reviewed. Novel physical illustrations are presented, including the cheese-cutting problem. A framework of space mapping steps is extracted.; Implicit Space Mapping (ISM) optimization exploits preassigned parameters. We introduce ISM and show how it relates to the now well-established (explicit) space mapping between coarse and fine device models. Through comparison a general space-mapping concept is proposed. A simple ISM algorithm is implemented. It is illustrated on the contrived "cheese-cutting problem" and applied to EM-based microwave modeling and design. An auxiliary set of parameters (selected preassigned parameters) is extracted to match the coarse model with the fine model. The calibrated coarse model (the surrogate) is then (re)optimized to predict an improved fine model solution. This is an easy SM technique to implement since the mapping itself is embedded in the calibrated coarse model and updated automatically in the procedure of parameter extraction.; We discuss the enhancement of the ISM by "output space" mapping (OSM) specifically, response residual space mapping (RRSM), when the model cannot be aligned. ISM calibrates a suitable coarse (surrogate) model against a fine model (full-wave EM simulation) by relaxing certain coarse model preassigned parameters. Based on an explanation of residual response misalignment, our new approach further fine-tunes the surrogate by the RRSM. (Abstract shortened by UMI.)...
Keywords/Search Tags:Space mapping, Model, Surrogate, Optimization, ISM, Output, Preassigned parameters, Fine
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