Investigation into the applications of genetic algorithms to control engineering

dc.contributor.advisorBraae, Martinen_ZA
dc.contributor.authorThithi, Thabang Ignatiousen_ZA
dc.date.accessioned2016-08-22T12:02:15Z
dc.date.available2016-08-22T12:02:15Z
dc.date.issued1996en_ZA
dc.descriptionBibliography: pages 117-120.en_ZA
dc.description.abstractThis thesis report presents the results of a study carried out to determine possible uses of genetic algorithms to problems in control engineering. This thesis reviewed the literature on the subject of genetics and genetic algorithms and applied the algorithms to the problems of systems parameter identification and Pl/D controller tuning. More specifically, the study had the following objectives: To investigate possible uses of genetic algorithms to the task of system identification and Pl/D controller tuning. To do an in depth comparison of the proposed uses with orthodox traditional engineering thinking which is based on mathematical optimisation and empirical studies. To draw conclusions and present the findings in the form of a thesis. Genetic algorithms are a class of artificial intelligence methods inspired by the Darwinian principles of natural selection and survival of the fittest. The algorithm encodes potential solutions into chromosome-like data structures that. are evolved using genetic ·operators to determine the optimal solution of the problem. Fundamentally, the evolutionary nature of the algorithm is introduced through the operators called crossover and mutation. Crossover fundamentally takes two strings, selects a crossing point randomly and swaps segments of the strings on either side of the crossover point to create two new individuals. There are three variations of crossover which were considered in this thesis: single point crossover, two point crossover and uniform crossover. It was important that these be given careful consideration since much of the outcome of the algorithm is influenced by both the choice and the amount with which they are applied.en_ZA
dc.identifier.apacitationThithi, T. I. (1996). <i>Investigation into the applications of genetic algorithms to control engineering</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/21394en_ZA
dc.identifier.chicagocitationThithi, Thabang Ignatious. <i>"Investigation into the applications of genetic algorithms to control engineering."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 1996. http://hdl.handle.net/11427/21394en_ZA
dc.identifier.citationThithi, T. 1996. Investigation into the applications of genetic algorithms to control engineering. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Thithi, Thabang Ignatious AB - This thesis report presents the results of a study carried out to determine possible uses of genetic algorithms to problems in control engineering. This thesis reviewed the literature on the subject of genetics and genetic algorithms and applied the algorithms to the problems of systems parameter identification and Pl/D controller tuning. More specifically, the study had the following objectives: To investigate possible uses of genetic algorithms to the task of system identification and Pl/D controller tuning. To do an in depth comparison of the proposed uses with orthodox traditional engineering thinking which is based on mathematical optimisation and empirical studies. To draw conclusions and present the findings in the form of a thesis. Genetic algorithms are a class of artificial intelligence methods inspired by the Darwinian principles of natural selection and survival of the fittest. The algorithm encodes potential solutions into chromosome-like data structures that. are evolved using genetic ·operators to determine the optimal solution of the problem. Fundamentally, the evolutionary nature of the algorithm is introduced through the operators called crossover and mutation. Crossover fundamentally takes two strings, selects a crossing point randomly and swaps segments of the strings on either side of the crossover point to create two new individuals. There are three variations of crossover which were considered in this thesis: single point crossover, two point crossover and uniform crossover. It was important that these be given careful consideration since much of the outcome of the algorithm is influenced by both the choice and the amount with which they are applied. DA - 1996 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1996 T1 - Investigation into the applications of genetic algorithms to control engineering TI - Investigation into the applications of genetic algorithms to control engineering UR - http://hdl.handle.net/11427/21394 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/21394
dc.identifier.vancouvercitationThithi TI. Investigation into the applications of genetic algorithms to control engineering. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 1996 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/21394en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleInvestigation into the applications of genetic algorithms to control engineeringen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc (Eng)en_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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