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      An Improved Hybrid Kalman Filter Design for Aircraft Engine based on a Velocity-Based LPV Framework

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      https://www.riss.kr/link?id=A103528745

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      다국어 초록 (Multilingual Abstract)

      In-flight aircraft engine performance estimation is one of the key techniques for advanced intelligent engine control and in-flight fault detection, isolation and accommodation. This paper detailed the current performance degradation estimation method...

      In-flight aircraft engine performance estimation is one of the key techniques for advanced intelligent engine control and in-flight fault detection, isolation and accommodation. This paper detailed the current performance degradation estimation methods, and an improved hybrid Kalman filter via velocity-based LPV (VLPV) framework for these needs is proposed in this paper. Composed of a nonlinear on-board model (NOBM) and VLPV, the filter shows a hybrid architecture. The outputs of NOBM are used for the baseline of the VLPV Kalman filter, while the system performance degradation factors on-line estimated by the measured real system output deviations are fed back to the NOBM for its updating. In addition, the setting of the process and measurement noise covariance matrices’ values are also discussed. By applying it to a commercial turbofan engine, simulation results show the efficiency.

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      목차 (Table of Contents)

      • Abstract
      • 1. Introduction
      • 2. An improved Kalman filter design procedure
      • 3. Simulations and applications
      • 4. Conclusions
      • Abstract
      • 1. Introduction
      • 2. An improved Kalman filter design procedure
      • 3. Simulations and applications
      • 4. Conclusions
      • References
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      참고문헌 (Reference)

      1 Leith, D.J, "Survey of gainscheduling analysis and design" 73 (73): 1001-1025, 2000

      2 Henrion, D, "Polynomial LPV synthesis applied to turbofan engines" Control Engineering Practice 1-7, 2008

      3 Leith, D.J, "On formulating nonlinear dynamics in LPV form" IEEE: Sydney 3526-3527, 2000

      4 Tanizaki, H, "Nonlinear filters: estimation and applications" Springer 1996

      5 Sommer, S, "Modeling a class of nonlinear plants as LPV-systems via nonlinear state-transformation" 2000

      6 Adibhatla, Shrider, "Model-based intelligent digital engine control (MoBIDEC)" 2013

      7 Kailath, T, "Linear systems" Prentice-Hall 1980

      8 Simon, T.K.D, "Hybrid Kalman Filter: A New Approach for Aircraft Engine In-Flight Diagnostics" NASA 2006

      9 Leith, D, "Gain-scheduled and nonlinear systems: dynamic analysis by velocity-based linearization families" 70 (70): 289-317, 1998

      10 Shamma, J.S, "Gain scheduling: Potential hazards and possible remedies" 12 (12): 101-107, 1992

      1 Leith, D.J, "Survey of gainscheduling analysis and design" 73 (73): 1001-1025, 2000

      2 Henrion, D, "Polynomial LPV synthesis applied to turbofan engines" Control Engineering Practice 1-7, 2008

      3 Leith, D.J, "On formulating nonlinear dynamics in LPV form" IEEE: Sydney 3526-3527, 2000

      4 Tanizaki, H, "Nonlinear filters: estimation and applications" Springer 1996

      5 Sommer, S, "Modeling a class of nonlinear plants as LPV-systems via nonlinear state-transformation" 2000

      6 Adibhatla, Shrider, "Model-based intelligent digital engine control (MoBIDEC)" 2013

      7 Kailath, T, "Linear systems" Prentice-Hall 1980

      8 Simon, T.K.D, "Hybrid Kalman Filter: A New Approach for Aircraft Engine In-Flight Diagnostics" NASA 2006

      9 Leith, D, "Gain-scheduled and nonlinear systems: dynamic analysis by velocity-based linearization families" 70 (70): 289-317, 1998

      10 Shamma, J.S, "Gain scheduling: Potential hazards and possible remedies" 12 (12): 101-107, 1992

      11 Bruzelius, F, "Gain scheduling via affine linear parameter-varying systems and H∞ synthesis" IEEE 3 : 2386-2391, 2001

      12 Packard, A, "Gain scheduling the LPV way" 4 : 3938-3941, 1997

      13 Gan, Q, "Fuzzy local linearization and local basis function expansion in nonlinear system modeling" 29 (29): 559-565, 1999

      14 Musoff, H, "Fundamentals of Kalman Filtering: A Practical Approach, Second Edition" 190 (190): 83-, 2005

      15 Luppold R, "Estimating inflight engine performance variations using Kalman filter concepts" 1989

      16 Volponi, A, "Enhanced Self-Tuning On-Board Real-Time Model (eSTORM) for Aircraft Engine Performance Health Tracking" NASA 2008

      17 Liu, X, "Design for Aircraft Engine Multiobjective Controllers with Switching Characteristics" 27 (27): 1097-1110, 2014

      18 Liu, X, "Approximate Nonlinear Modeling of Aircraft Engine Surge Margin Based on Equilibrium Manifold Expansion" 25 (25): 663-674, 2012

      19 Wolodkin, G, "Application of Parameter-Dependent Robust Control Synthesis to Turbofan Engines" 22 (22): 833-838, 1998

      20 Rugh, W.J, "Analytical framework for gain scheduling" 11 (11): 79-84, 1991

      21 Shamma, J.S, "Analysis of gain scheduled control for nonlinear plants" 35 (35): 898-907, 1990

      22 Shamma, J.S, "Analysis and design of gain scheduled control systems" Massachusetts Institute of Technology 1988

      23 Simon, Dan, "Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering" 127 (127): 1930-1934, 2003

      24 Whatley, M.J, "Adaptive gain improves reactor control" 63 (63): 75-78, 1984

      25 Apkarian, P, "A convex characterization of gain-scheduled H∞ controllers" 40 (40): 853-864, 1995

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      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2013-10-01 평가 등재학술지 선정 (기타) KCI등재
      2011-01-01 평가 등재후보학술지 선정 (기타) KCI등재후보
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      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.37 0.2 0.3
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.26 0.24 0.394 0.03
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