Time-domain optimization of amplifiers based on distributed genetic algorithms

Bibliographic Details
Main Author: Tavares, Rui Manuel Leitão Santos
Publication Date: 2010
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/5061
Summary: Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
id RCAP_5840b947f19a5eacf09e4390b97f95eb
oai_identifier_str oai:run.unl.pt:10362/5061
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Time-domain optimization of amplifiers based on distributed genetic algorithmsThesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer EngineeringThe work presented in this thesis addresses the task of circuit optimization, helping the designer facing the high performance and high efficiency circuits demands of the market and technology evolution. A novel framework is introduced, based on time-domain analysis, genetic algorithm optimization, and distributed processing. The time-domain optimization methodology is based on the step response of the amplifier. The main advantage of this new time-domain methodology is that, when a given settling-error is reached within the desired settling-time, it is automatically guaranteed that the amplifier has enough open-loop gain, AOL, output-swing (OS), slew-rate (SR), closed loop bandwidth and closed loop stability. Thus, this simplification of the circuit‟s evaluation helps the optimization process to converge faster. The method used to calculate the step response expression of the circuit is based on the inverse Laplace transform applied to the transfer function, symbolically, multiplied by 1/s (which represents the unity input step). Furthermore, may be applied to transfer functions of circuits with unlimited number of zeros/poles, without approximation in order to keep accuracy. Thus, complex circuit, with several design/optimization degrees of freedom can also be considered. The expression of the step response, from the proposed methodology, is based on the DC bias operating point of the devices of the circuit. For this, complex and accurate device models (e.g. BSIM3v3) are integrated. During the optimization process, the time-domain evaluation of the amplifier is used by the genetic algorithm, in the classification of the genetic individuals. The time-domain evaluator is integrated into the developed optimization platform, as independent library, coded using C programming language. The genetic algorithms have demonstrated to be a good approach for optimization since they are flexible and independent from the optimization-objective. Different levels of abstraction can be optimized either system level or circuit level. Optimization of any new block is basically carried-out by simply providing additional configuration files, e.g. chromosome format, in text format; and the circuit library where the fitness value of each individual of the genetic algorithm is computed. Distributed processing is also employed to address the increasing processing time demanded by the complex circuit analysis, and the accurate models of the circuit devices. The communication by remote processing nodes is based on Message Passing interface (MPI). It is demonstrated that the distributed processing reduced the optimization run-time by more than one order of magnitude. Platform assessment is carried by several examples of two-stage amplifiers, which have been optimized and successfully used, embedded, in larger systems, such as data converters. A dedicated example of an inverter-based self-biased two-stage amplifier has been designed, laid-out and fabricated as a stand-alone circuit and experimentally evaluated. The measured results are a direct demonstration of the effectiveness of the proposed time-domain optimization methodology.Portuguese Foundation for the Science and Technology (FCT)Faculdade de Ciências e TecnologiaPaulino, NunoGoes, JoãoRUNTavares, Rui Manuel Leitão Santos2011-02-09T09:41:42Z20102010-01-01T00:00:00Zdoctoral thesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10362/5061enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:08:20Zoai:run.unl.pt:10362/5061Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:39:20.105566Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Time-domain optimization of amplifiers based on distributed genetic algorithms
title Time-domain optimization of amplifiers based on distributed genetic algorithms
spellingShingle Time-domain optimization of amplifiers based on distributed genetic algorithms
Tavares, Rui Manuel Leitão Santos
title_short Time-domain optimization of amplifiers based on distributed genetic algorithms
title_full Time-domain optimization of amplifiers based on distributed genetic algorithms
title_fullStr Time-domain optimization of amplifiers based on distributed genetic algorithms
title_full_unstemmed Time-domain optimization of amplifiers based on distributed genetic algorithms
title_sort Time-domain optimization of amplifiers based on distributed genetic algorithms
author Tavares, Rui Manuel Leitão Santos
author_facet Tavares, Rui Manuel Leitão Santos
author_role author
dc.contributor.none.fl_str_mv Paulino, Nuno
Goes, João
RUN
dc.contributor.author.fl_str_mv Tavares, Rui Manuel Leitão Santos
description Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
publishDate 2010
dc.date.none.fl_str_mv 2010
2010-01-01T00:00:00Z
2011-02-09T09:41:42Z
dc.type.driver.fl_str_mv doctoral thesis
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/5061
url http://hdl.handle.net/10362/5061
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596088886493184

Similar Items