• Title/Summary/Keyword: Markovian model

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Stochastic Stabilization of TS Fuzzy System with Markovian Input Delay (마코프 입력 지연 시스템의 확률적 안정화)

  • Lee, Ho-Jae;Park, Jin-Bae;Lee, Sang-Youn;Joo, Young-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.153-156
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    • 2001
  • This paper discusses a stochastic stabilization of Takagi-Sugeno (75) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time 75 fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized 75 fuzzy system is represented by a discrete-time 75 fuzzy system with jumping parameters. The stochastic stabilizibility of the jump 75 fuzzy system is derived and formulated in terms of linear matrix inequalities (LMls).

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Markovian Approach of Inspection Policy in a Serial Manufacturing System (Markovian 접근방법을 이용한 직렬생산시스템의 검사정책)

  • 정영배;황의철
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.11 no.17
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    • pp.81-85
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    • 1988
  • This paper presents a model that considers combinations of rework, repair, replacement and scrapping. Policy-Iteration method of inspection is proposed for a serial manufacturing system whose repair cost, scrap cost and inspection cost. when it fails, can be formulated by Markovian approach. Policy-Iteration stops when new inspection policy is the same as previous inspection policy. A numerial example is presented.

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The BMAP/G/1Queue with Correlated Flows of Customers and Disasters

  • Kim, Che-Soong
    • Journal of Korea Society of Industrial Information Systems
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    • v.10 no.2
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    • pp.42-47
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    • 2005
  • A single-server queueing model with the Batch Markovian Arrival Process and disaster ow correlated with the arrival process is analyzed. The numerically stable algorithm for calculating the steady state distribution of the system is presented.

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Observer-Based Output Feedback Stochastic Stabilization for T-S Fuzzy Systems with Input Delay (입력지연을 갖는 T-S 퍼지 시스템의 관측기기반 출력궤환 확률적 안정화)

  • Lee, Sang In;Park, Jin Bae;Joo, Young Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.298-303
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    • 2004
  • This paper deals with a stochastic stabilization of observer-based output-feedback control Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The stochastic stabilizability of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). The usefulness of the proposed algorithm is also certificated by simulation of 2 degree of freedom helicopter model.

Predicting the Score of a Soccer Match by Use of a Markovian Arrival Process (마코비안 도착과정을 이용한 축구경기 득점결과의 예측)

  • Kim, Nam-Ki;Park, Hyun-Min
    • IE interfaces
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    • v.24 no.4
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    • pp.323-329
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    • 2011
  • We develop a stochastic model to predict the score of a soccer match. We describe the scoring process of the soccer match as a markovian arrival process (MAP). To do this, we define a two-state underlying Markov chain, in which the two states represent the offense and defense states of the two teams to play. Then, we derive the probability vector generating function of the final scores. Numerically inverting this generating function, we obtain the desired probability distribution of the scores. Sample numerical examples are given at the end to demonstrate how to utilize this result to predict the final score of the match.

Intelligent Controller for Networked Control Systems with Time-delay (시간지연을 갖는 네트워크 제어 시스템의 지능형 제어기 설계)

  • Bae, Gi-Sun;Joo, Young-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.2
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    • pp.139-144
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    • 2011
  • We consider the stabilization problem for a class of networked control systems with random delays in the discrete-time domain. The controller-to-actuator and sensor-to-controller time-delays are modeled as two Markov chains, and the resulting closed-loop systems are Markovian jump nonlinear systems with two modes. The T-S (Takagi-Sugeno) fuzzy model is employed to represent a nonlinear system with Markovian jump parameters. The aim is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. The necessary and sufficient conditions on the existence of stabilizing fuzzy controllers are established in terms of LMIs (Linear Matrix Inequalities). It is shown that fuzzy controller gains are mode-dependent. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.

A NON-MARKOVIAN EVOLUTION MODEL OF HIV POPULATION WITH BUNCHING BEHAVIOUR

  • Sridharan, V.;Jayshree, P.R.
    • Journal of applied mathematics & informatics
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    • v.5 no.3
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    • pp.785-796
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    • 1998
  • In this paper we propose a model of HIv population through method of phases with non-Markovian evolution of immi-gration. The analysis leads to an explicit differnetial equations for the generating functions of the total population size. The detection process of antibodies (against the antigen of virus) is analysed and an explicit expression for the correlation functions are provided. A measure of bunching is also introduced for some particular choice of parameters.

Performance Evaluation of Software Task Processing Based on Markovian Perfect Debugging Model

  • Lee, Chong-Hyung;Jang, Kyu-Beam;Park, Dong-Ho
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.997-1006
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    • 2008
  • This paper proposes a new model by combining an infinite-server queueing model for multi-task processing software system with a perfect debugging model based on Markov process with two types of faults suggested by Lee et al. (2001). We apply this model for module and integration testing in the testing process. Also, we compute several measure, such as the expected number of tasks whose processes can be completed and the task completion probability are investigated under the proposed model.

Stochastic Stabilization of TS Fuzzy System with Markovian Input Delay (마코프 입력 지연을 갖는 TS 퍼지 시스템의 확률전 안정화)

  • 이호재;주영훈;이상윤;박진배
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.6
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    • pp.459-464
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    • 2001
  • This paper discusses a stochastic stabilization of Takagi-Sugeno(TS) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delary of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time TS fuzzy system with the Markovian input delay is discretized for easy handling delay, according, the discretized TS fuzzy system is represented by a discrete-time TS fuzzy system with jumping parameters. The stochastic stabilizibility of the jump TS fuzzy system is derived and formulated in terms of linear matrix inequalities (LNIS)

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Markovian Perfect Debugging Model and Its Related Measures

  • Lee Chong Hyung;Nam Kyung Hyun;Park Dong Ho
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.57-64
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    • 2000
  • In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model, Numerical examples are provided for illustrative purposes.

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