The design of a dual reflector feed using surrogate modeling techniques

Vermeulen, Alexander Alfons (2016-03)

Thesis (MEng)--Stellenbosch University, 2016.

Thesis

ENGLISH ABSTRACT: The optimisation of a feed horn for a dual Gregorian reflector antenna system using surrogate modelling was investigated. This included a brief overview of dual reflector antenna systems as well as their performance parameters. The design for a three axial choke horn with a variety of matching sections was described for use with the optimisation. Two techniques were investigated, namely space mapping (SM) and a Kriging interpolate based approach. The SM technique consisted of augmenting a fast coarse model by aligning it to a slow fine model. This showed potential but was ultimately hampered by the lack of a coarse model that did not require a full wave simulation for the primary feed pattern and so was abandoned. The interpolation based technique could use two approaches. The first consisted of an interpolate based on a coarse data set that was then corrected using a regression model based on the difference between the fine and coarse model at a few training sits. The second approach consisted of only an interpolate that was based on a fine data set. The technique was applied to a multi-objective optimisation (MOO) problem. The optimisation aimed at minimizing the reflection coeficient and maximizing the sensitivity of the reflector system. It was shown to work well and produced reasonably accurate results while reducing the total optimisation time from potentially weeks or months down to the order of a day. As part of the investigation an MOO algorithm called multi-objective population based incremental learning (MOPBIL) was implemented. The basic concepts of MOO and MOPBIL were discussed and the implementation was described. This implementation was also fully tested and shown to approximate the Pareto front well.

AFRIKAANSE OPSOMMING: Die optimering van 'n voerhoering vir 'n dubbelweerkaatser Gregoriaanse antennastelsel wat gebruik maak van 'n surrogaat model was geondersoek. Dit het 'n kort oorsig ingesluit van die dubbelweerkaatser antennastelsels asook die prestasie grense daarvan. Die ontwerp van 'n horing antenna met drie aksiale smoorder, vir verskeie tipes aanpassingseksies, is beskryf vir gebruik in die optimeringstrategie. Twee tegnieke was ondersoek, naamlik spasie kartering (SK) en 'n Kriging interpolasie-gebaseerde benadering. Die SK tegniek het bestaan uit die verfyning van 'n vinnige growwe model deur die aanpassing daarvan na 'n stadige fyn model. Dit het potensiaal getoon, maar is uiteindelik laat vaar as gevolg van 'n gebrek aan 'n growwe model wat nie 'n volgolf simulasie vir die primêre voer patroon benodig nie. Die interpolasie gebaseerde tegniek kon twee benaderings gebruik. Die eerste het bestaan uit 'n interpolasie gebaseer op 'n growwe datastel wat dan reggestel was met behulp van 'n regressiemodel gebaseer op die verskil tussen die fyn en growwe model soos gevind by 'n paar opleidingspunte. Die tweede benadering het slegs bestaan uit 'n interpolasie wat gebaseer was op 'n fyn datastel. Die tegniek was toegepas op 'n multi-doel optimeringsprobleem (MO). Die optimering was gemik daarop om die stelsel se weerkaatsings-koëffisiënt te minimeer sowel as om die sensitiwiteit te maksimeer. Die laasgenoemde benadering het aanduiding gegee dat dit goed werk deur redelike akkurate resultate te lewer terwyl die totale optimeringstyd van moontlike weke of maande na so min as 'n dag verminder was. As deel van die ondersoek was 'n MO algoritme wat bekend staan as 'Multi-objective population based incremental learning' (MOPBIL) geïmplementeer. Die basiese konsepte van MO en MOPBIL was bespreek en die implementering was beskryf. Hierdie implementering was ook ten volle getoets en resultate het gewys dat dit die Pareto front goed benader.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/98492
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