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BCOR 접근법을 이용한 클라우드 컴퓨팅 도입의 의사결정 요인에 관한 연구
이영찬(Young-Chan Lee),당응웬하인(Tang Nguyen Hanh) 한국IT서비스학회 2012 한국IT서비스학회지 Vol.11 No.1
With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners’ effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.
Simplified model prediction current control strategy for permanent magnet synchronous motor
Zhang, Housheng,Zhu, Shengjie,Jiang, Junjie,Wang, Qingzhuang,Wang, Ao,Jin, Duo The Korean Institute of Power Electronics 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.11
A simplified model predictive current control strategy based on mathematical auxiliary line method is proposed to increase the permanent magnet synchronous motor (PMSM) predictive current control system's steady-state performance while reducing the system's computational complexity. The mathematical models of current prediction, first-order compensation, and cost function are presented by analyzing the prediction current control strategy of the conventional models. Within a control cycle, the simplified model predictive current control algorithm applies two voltage vectors and omits the error calculation of cost function. The anticipated voltage of transformer obtained from the beat-free current control standard is considered the reference voltage, and the judgment of the area, where the reference voltage vector is found and the strategy for double voltage vector is selected, is put forward. The optimal voltage vector can be directly output without the error calculation of the cost function in the method, thereby effectively reducing the computation load and complexity of the system and improving the steady-state performance. Experimental results verify the validity and accuracy of the proposed simplified model of predictive current control strategy for PMSM control.