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The defense date of the thesis is 2015-09-04
The current date is 2019-05-24
This thesis will be accessible at 2020-09-04
URN etd-0904115-115802 Statistics This thesis had been viewed 396 times. Download 0 times. Author Wei-Lun Huang Author's Email Address No Public. Department Electrical Engineering Year 2014 Semester 2 Degree Master Type of Document Master's Thesis Language zh-TW.Big5 Chinese Page Count 59 Title DIFFERENTIAL EVOLUTION WITH ADAPTIVE WINNER MUTATION STRATEGY FOR PID CONTROLLER OPTIMIZATION Keyword current-to-winner benchmark function parameter adaption control parameter control parameter parameter adaption benchmark function current-to-winner Abstract This thesis base on winner mutation strategy, proposed current-to-winner mutation strategy. Traditional mutation strategies have the most suitable control parameters-mutation factor and crossover rate, but during the search need lots of experience to adjust the control parameters to the most suitable value. Therefore, this thesis join parameter adaption to make the algorithm can not only renew the control parameters automatically but also avoid lots of experience on adjusting control parameters. The proposed mutation strategy for different benchmark functions, joining the parameter adaptation adjustment method so that can improve algorithm’s performance. Simulation results show that the mutation strategy has good searching ability, also can achieve good control performance. Advisor Committee Hung-Ching Lu - advisor
Files Date of Defense 2015-07-22 Date of Submission 2015-09-04