On the realization of an accurate control system using a discrete iterative learning control method이산 반복 학습 제어 방법을 이용한 정밀 추종 제어 시스템의 구현에 관한 연구

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dc.contributor.advisorCho, Hyung-Suck-
dc.contributor.advisor조형석-
dc.contributor.authorPark, Hee-Jae-
dc.contributor.author박희재-
dc.date.accessioned2011-12-14T05:09:37Z-
dc.date.available2011-12-14T05:09:37Z-
dc.date.issued1991-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=61836&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/42494-
dc.description학위논문(박사) - 한국과학기술원 : 생산공학과, 1991.8, [ 1책(면수복잡) ; ]-
dc.description.abstractTo realize an accurate tracking control system, various discrete iterative learning control algorithms have been developed for 1) a class of linear time-varying systems, 2) a class of system subjected to unknown disturbance, 3) a system whose state variables are difficult to measure, 4) a system on which mathematical modeling is difficult and only vague and imprecise information is abailble. To this end, we employ the well known technologies 1) Prarmeter extimation shcemes which estimate parameters of the inverse system model and the unknown disturbances, 2) Fuzzy set theory by which human thinking and natural language can be imposed to the iterative learning controller. To investigate the validity of the proposed algorithms, the propsed iterative control algorithms were implemented to the systems 1) Electric servo moter system, 2) Robot manipulator, 3) Hydraulic servo system, 4) Hydrogorming process. The following facts can be observed from the experimental results 1) The proposed algorithm provides high tracking accuracy in comparison with other conventional controllers since additional control input attained from learning eliminates the error due to the unknown factors of the system to be controlled, 2) Monotomic and uniform convergence can be obtained by adjusting the input modification factor, 3) The proposed algorithm successfully come up with the environment change owing to the built-in self improvement mechansim, 4) The proposed algorithm can effectively cope with unknown external disturbance since the disturbance is estimated as the operation is proceeded, 5) The proposed algorithm can be applied to the system using the output measurements instead of state variable. 6) The proposed algorithm can be easily designed for a complex and ill-defined processes by using the vague and qualitative experiences of perators or knowledge of the control engineers. Form the promising results, it has been found that the machine with the proposed learning algortithm can...eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.titleOn the realization of an accurate control system using a discrete iterative learning control method-
dc.title.alternative이산 반복 학습 제어 방법을 이용한 정밀 추종 제어 시스템의 구현에 관한 연구-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN61836/325007-
dc.description.department한국과학기술원 : 생산공학과, -
dc.identifier.uid000875806-
dc.contributor.localauthorCho, Hyung-Suck-
dc.contributor.localauthor조형석-
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ME-Theses_Ph.D.(박사논문)
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