Optimization of control parameters for fluid power systems by genetic algorithms = 유전 알고리즘을 이용한 유공압 시스템 제어 파라미터 최적화

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 235
  • Download : 0
DC FieldValueLanguage
dc.contributor.advisorLee, Chung-Oh-
dc.contributor.advisor이정오-
dc.contributor.authorAhn, Choul-Hyun-
dc.contributor.author안철현-
dc.date.accessioned2011-12-14T06:57:59Z-
dc.date.available2011-12-14T06:57:59Z-
dc.date.issued1996-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=105445&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/46539-
dc.description학위논문(석사) - 한국과학기술원 : 기계공학과, 1996.2, [ vi, 46 p. ]-
dc.description.abstractThis thesis presents a genetic algorithm-based method for optimizing control parameters for fluid power systems. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics. A genetic algorithm seeks control parameters that maximize a measure that evaluates system performance. Gains of a state feedback controller for an electropneumatic position control system and gains of a PID-PD cascade controller for an electrohydraulic speed control system were optimized by a genetic algorithm within reasonable number of experiments. It is concluded that genetic algorithms are efficient for optimizing control parameters for fluid power system.eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectHydraulic-
dc.subjectGains-
dc.subjectGenetic algorithms-
dc.subjectFluid power systems-
dc.subjectControl parameters-
dc.subjectOptimization-
dc.subjectPneumatic-
dc.subject공압-
dc.subject유압-
dc.subject게인-
dc.subject유전 알고리즘-
dc.subject유공압 시스템-
dc.subject제어 파라미터-
dc.subject최적화-
dc.titleOptimization of control parameters for fluid power systems by genetic algorithms = 유전 알고리즘을 이용한 유공압 시스템 제어 파라미터 최적화-
dc.typeThesis(Master)-
dc.identifier.CNRN105445/325007-
dc.description.department한국과학기술원 : 기계공학과, -
dc.identifier.uid000943316-
dc.contributor.localauthorLee, Chung-Oh-
dc.contributor.localauthor이정오-
Appears in Collection
ME-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0