Date of Award
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
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 Broydenbased 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 cheesecutting 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. We present an RRSM approach. A novel, simple "multiple cheese-cutting" problem illustrates the technique. The approach is implemented entirely in the Agilent ADS design environment. A new design framework which implements various SM techniques is presented. We demonstrate the steps, for microwave devices, within the ADS (2003) schematic design framework. The design steps are friendly. The framework runs with Agilent Momentum, HFSS and Sonnet em. Finally, we review various engineering applications and implementations of the SM technique.
Cheng, Qingsha S., "Advances in Space Mapping Technology Exploiting Implicit Space Mapping and Output Space Mapping" (2004). Open Access Dissertations and Theses. Paper 1603.