A Space-Mapping Framework for Engineering Optimization-Theory and Implementation

This paper presents a comprehensive approach to engineering design optimization exploiting space mapping (SM). The algorithms employ input SM and a new generalization of implicit SM to minimize the misalignment between the coarse and fine models of the optimized object over a region of interest. Out...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 2006-10, Vol.54 (10), p.3721-3730
Main Authors: Koziel, S., Bandler, J.W., Madsen, K.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Band pass filters
Bandpass filters
Circuit properties
Computer-aided design (CAD)
Convergence
Derivatives
design automation
Design engineering
Design optimization
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
engineering optimization
Exact sciences and technology
Frequency filters
Impedance
Microstrip filters
Microstrip resonators
Microwave circuits, microwave integrated circuits, microwave transmission lines, submillimeter wave circuits
Microwaves
Optimization
Oscillators, resonators, synthetizers
Resonators
Samarium
Signal convertors
Software algorithms
Software packages
space mapping (SM)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents a comprehensive approach to engineering design optimization exploiting space mapping (SM). The algorithms employ input SM and a new generalization of implicit SM to minimize the misalignment between the coarse and fine models of the optimized object over a region of interest. Output SM ensures the matching of responses and first-order derivatives between the mapped coarse model and the fine model at the current iteration point in the optimization process. We provide theoretical results that show the importance of the explicit use of sensitivity information to the convergence properties of our family of algorithms. Our algorithm is demonstrated on the optimization of a microstrip bandpass filter, a bandpass filter with double-coupled resonators, and a seven-section impedance transformer. We describe the novel user-oriented software package SMF that implements the new family of SM optimization algorithms
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2006.882894