• Title/Summary/Keyword: adaptive model

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Improving Performance of HMIPv6 Networks with Adaptive TUE Selection Scheme (적응적 MAP 선택을 통한 HMIPv6 네트워크의 성능 향상 알고리즘)

  • Chung, Won-Sik;Lee, Su-Kyoung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.11B
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    • pp.945-952
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    • 2006
  • In hierarchical mobile IPv6 networks, when an inter-domain handover occurs, mobile nodes suffer from excessive signaling traffic and long handover latency, resulting in possible disruption of ongoing connections. Further, the selection of MAP and its load status critically affect the overall system performance. Therefore, we propose a dynamic MAP selection scheme that seeks to distribute load among MAPs as well as reduces inter-domain handovers. Performance is evaluated from not only an analytic model of average signaling cost but also simulation. The analytical and simulation results show that our proposed scheme improves load distributedness and reduces inter-domain handovers and signaling cost compared to another existing IETF based approach.

Pressure Control Law of Gas Generator Considering Combustion Volume Change (연소공간 변화를 보상하는 가스발생기 압력 제어기법)

  • Park, Ik-Soo;Lee, Jae-Yoon;Choi, Ho-Jin;Kim, Jung-Hoe;Yoon, Hyun-Gull;Lim, Jin-Shik
    • Journal of the Korean Society of Propulsion Engineers
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    • v.16 no.3
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    • pp.34-40
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    • 2012
  • A pressure control law to regulate pressure of gas generator is suggested. To design a model based control law, the governing equation which consists of Robert and conservation equation is built and verified through the ground burning test. PID and nonlinear adaptive control laws are designed to analyze the loop response characteristics under the system which has varying eigen properties arisen from combustion volume change. It is suggested that new approach, gain scheduling design, is required to overcome the defects identified from numerical simulation results of the two control laws. The newly suggested scheme shows good control performance even under disturbances and measurement noise.

Application of the ANFIS model in deflection prediction of concrete deep beam

  • Mohammadhassani, Mohammad;Nezamabadi-Pour, Hossein;Jumaat, MohdZamin;Jameel, Mohammed;Hakim, S.J.S.;Zargar, Majid
    • Structural Engineering and Mechanics
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    • v.45 no.3
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    • pp.323-336
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    • 2013
  • With the ongoing development in the computer science areas of artificial intelligence and computational intelligence, researchers are able to apply them successfully in the construction industry. Given the complexities indeep beam behaviour and the difficulties in accurate evaluation of its deflection, the current study has employed the Adaptive Network-based Fuzzy Inference System (ANFIS) as one of the modelling tools to predict deflection for high strength self compacting concrete (HSSCC) deep beams. In this study, about 3668measured data on eight HSSCC deep beams are considered. Effective input data and the corresponding deflection as output data were recorded at all loading stages up to failure load for all tested deep beams. The results of ANFIS modelling and the classical linear regression were compared and concluded that the ANFIS results are highly accurate, precise and satisfactory.

Mobility Prediction Algorithms Using User Traces in Wireless Networks

  • Luong, Chuyen;Do, Son;Park, Hyukro;Choi, Deokjai
    • Journal of Korea Multimedia Society
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    • v.17 no.8
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    • pp.946-952
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    • 2014
  • Mobility prediction is one of hot topics using location history information. It is useful for not only user-level applications such as people finder and recommendation sharing service but also for system-level applications such as hand-off management, resource allocation, and quality of service of wireless services. Most of current prediction techniques often use a set of significant locations without taking into account possible location information changes for prediction. Markov-based, LZ-based and Prediction by Pattern Matching techniques consider interesting locations to enhance the prediction accuracy, but they do not consider interesting location changes. In our paper, we propose an algorithm which integrates the changing or emerging new location information. This approach is based on Active LeZi algorithm, but both of new location and all possible location contexts will be updated in the tree with the fixed depth. Furthermore, the tree will also be updated even when there is no new location detected but the expected route is changed. We find that our algorithm is adaptive to predict next location. We evaluate our proposed system on a part of Dartmouth dataset consisting of 1026 users. An accuracy rate of more than 84% is achieved.

Improved MOG Algorithm for Periodic Background (주기성 배경을 위한 개선된 MOG 알고리즘)

  • Jeong, Yong-Seok;Oh, Jeong-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.10
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    • pp.2419-2424
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    • 2013
  • In a conventional MOG algorithm, a small threshold for background decision causes the background recognition delay in a periodic background and a large threshold makes it recognize passing objects as background in a stationary background. This paper proposes the improved MOG algorithm using adaptive threshold. The proposed algorithm estimates changes of weight in the dominant model of the MOG algorithm both in the short and long terms, classifies backgrounds into the stationary and periodic ones, and assigns proper thresholds to them. The simulation results show that the proposed algorithm decreases the maximum number of frame in background recognition delay from 137 to 4 in the periodic background keeping the equal performance with the conventional algorithm in the stationary background.

External Noise Analysis Algorithm based on FCM Clustering for Nonlinear Maneuvering Target (FCM 클러스터링 기반 비선형 기동표적의 외란분석 알고리즘)

  • Son, Hyun-Seung;Park, Jin-Bae;Joo, Young-Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.12
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    • pp.2346-2351
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    • 2011
  • This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

The design of hybrid control system using Fuzzy and AFC (퍼지 및 AFC를 이용한 복합 제어시스템 설계)

  • Kim, Gwan-Hyung;Jeong, Hoi-Seong;Kim, Jun-Su;Cho, Hyun-Cheol;Lee, Hyung-Ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.545-546
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    • 2012
  • 일반적으로 회전력이 발생하는 제어시스템에 있어서 발생되는 외란과 시스템의 동특성에 의해 발생되는 리플 등을 보정하기 위해 다양한 제어기법들이 연구되고 있다. 특히, 제어시스템에 존재하는 미지의 외란을 제거하기 위하여 AFC(Adaptive Feedforward Cancellation) 제어이론을 적용하여 미지의 외란에 대한 시스템의 안정성을 확보하려고 노력하고 있다. 그러나 기존의 AFC의 구현을 위하여 연속 시간제어시스템의 전달함수인 IMP(Internal Model Principle)를 이용하여 특정 주파수 영역에 대한 외란을 제거하고 있지만 보다 광범위한 영역에 대해서는 제어 성능은 아직 부족한 편이다. 본 논문에서는 기존의 PID 제어기를 이용한 위치제어에 있어서 발생할 수 있는 외란을 제거하기 위해 AFC 제어이론인 IMP 전달함수와 인공지능 기법인 Fuzzy 제어기를 추가로 설계하여 모터의 위치제어에 대한 성능과 외란 제어에 대한 성능을 제시하고자 한다.

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A Novel Discrete-Time Predictive Current Control for PMSM

  • Sun, Jung-Won;Suh, Jin-Ho;Lee, Young-Jin;Lee, Kwon-Soon
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1915-1919
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    • 2004
  • In this paper, we propose a new discrete-time predictive current controller for a PMSM(Permanent Magnet Synchronous Motor). The main objectives of the current controllers are to ensure that the measured stator currents tract the command values accurately and to shorten the transient interval as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that it takes to apply the voltage to motor. A new control strategy in this paper is seen the scheme that gets the fast adaptation of transient current change, the fast transient response tracking and is proposed simplified calculation. Moreover, the validity of the proposed method is demonstrated by numerical simulations and the simulation results will be verified the improvements of predictive controller and accuracy of the current controller.

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Adaptive User Profile for Information Retrieval from the Web

  • Srinil, Phaitoon;Pinngern, Ouen
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1986-1989
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    • 2003
  • This paper proposes the information retrieval improvement for the Web using the structure and hyperlinks of HTML documents along with user profile. The method bases on the rationale that terms appearing in different structure of documents may have different significance in identifying the documents. The method partitions the occurrence of terms in a document collection into six classes according to the tags in which particular terms occurred (such as Title, H1-H6 and Anchor). We use genetic algorithm to determine class importance values and expand user query. We also use this value in similarity computation and update user profile. Then a genetic algorithm is used again to select some terms from user profile to expand the original query. Lastly, the search engine uses the expanded query for searching and the results of the search engine are scored by similarity values between each result and the user profile. Vector space model is used and the weighting schemes of traditional information retrieval were extended to include class importance values. The tested results show that precision is up to 81.5%.

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The Implementation of Agile SFFS using 5DOF Robot

  • Kim, Seung-Woo;Jung, Yong-Rae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.716-721
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    • 2004
  • Several Solid Freeform Fabrication Systems(SFFS) are commercialized in a few companies for rapid prototyping. However, they have many technical problems including the limitation of applicable materials. A new method of speedy prototyping is required for the recent manufacturing environments of multi-item and small quantity production. The objectives of this paper include the development of a novel method of SFFS, the ${CAFL}^{VM}$(Computer Aided Fabrication of Lamination for Various Material), and the manufacture of the various material samples for the certification of the proposed system and the creation of new application areas. For these objectives, the technologies for a highly accurate robot path control, the optimization of support structure, CAD modeling, adaptive slicing was implemented. In this paper, we design an algorithm that the cutting path of a laser beam which is controlled with constant speed. The laser beam is tangentially controlled in order to solve the inaccuracy of a 3D model surface. The designed algorithm for constant-speed path control and tangent-cutting control is implemented and experimented in the ${CAFL}^{VM}$ system.

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