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      KCI등재 SCIE

      Identification of Unknown Parameter Value for Precise Flow Control of Coupled Tank using Robust Unscented Kalman Filter

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      https://www.riss.kr/link?id=A103559537

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      다국어 초록 (Multilingual Abstract)

      In this paper, we consider the problems of state estimation and parameter estimation. The goal is to consider Robust Unscented Kalman filter, and demonstrate their successful application on a Coupled Tank system. Traditional unscented kalman filter ha...

      In this paper, we consider the problems of state estimation and parameter estimation. The goal is to consider Robust Unscented Kalman filter, and demonstrate their successful application on a Coupled Tank system. Traditional unscented kalman filter have a limitation to estimate the state and parameter of time-varying parameter system due to making use of fixed measurement covariance without updating measurement error between measured data and estimated data. Proposed method is Robust Unscented Kalman filter to perform the estimation of the changing parameter value. A structure of the Coupled Tank System consists of connected two tank with basin. The other goal is to make use of the considered filtering method to compare between the other methods. Extensive experiments by numerical simulations and experimentation using real hardware are performed. The study of the experimental results shows a proposed method concern various aspects, such as estimation accuracy, convergence speed, and the accuracy of estimating fixed parameter values. Overall, the proposed Unscented Kalman filter turned out the best of the other considered methods.

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      참고문헌 (Reference)

      1 Matta, E., "Unscented Kalman Filter for Non-Linear Identification of a New Prototype of Bidirectional Tuned Vibration Absorber : A Numerical Investigation" 569-570 (569-570): 948-955, 2013

      2 Alkaya, A., "Unscented Kalman Filter Performance for Closed-Loop Nonlinear State Estimation : A Simulation Case Study" 96 (96): 299-308, 2014

      3 Chatzi, E. N., "The Unscented Kalman Filter and Particle Filter Methods for Nonlinear Structural System Identification with Non-Collocated Heterogeneous Sensing" 16 (16): 99-123, 2009

      4 Aksoy, S., "State and Parameter Estimation in Induction Motor using the Extended Kalman Filtering Algorithm" 1-5, 2010

      5 Lichter, M. D., "Shape, Motion, and Parameter Estimation of Large Flexible Space Structures using Range Images" 4476-4481, 2005

      6 Xie, Z., "Real-Time Nonlinear Structural System Identification via Iterated Unscented Kalman Filter" 28 : 309-322, 2012

      7 Oh, S. -K., "Parameter Estimation of Fuzzy Controller and Its Application to Inverted Pendulum" 17 (17): 37-60, 2004

      8 Swevers, J., "Optimal Robot Excitation and Identification" 13 (13): 730-740, 1997

      9 Daum, F., "Nonlinear Filters : Beyond the Kalman Filter" 20 (20): 57-69, 2005

      10 Orlowska-Kowalska, T., "Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System" 54 (54): 1352-1364, 2007

      1 Matta, E., "Unscented Kalman Filter for Non-Linear Identification of a New Prototype of Bidirectional Tuned Vibration Absorber : A Numerical Investigation" 569-570 (569-570): 948-955, 2013

      2 Alkaya, A., "Unscented Kalman Filter Performance for Closed-Loop Nonlinear State Estimation : A Simulation Case Study" 96 (96): 299-308, 2014

      3 Chatzi, E. N., "The Unscented Kalman Filter and Particle Filter Methods for Nonlinear Structural System Identification with Non-Collocated Heterogeneous Sensing" 16 (16): 99-123, 2009

      4 Aksoy, S., "State and Parameter Estimation in Induction Motor using the Extended Kalman Filtering Algorithm" 1-5, 2010

      5 Lichter, M. D., "Shape, Motion, and Parameter Estimation of Large Flexible Space Structures using Range Images" 4476-4481, 2005

      6 Xie, Z., "Real-Time Nonlinear Structural System Identification via Iterated Unscented Kalman Filter" 28 : 309-322, 2012

      7 Oh, S. -K., "Parameter Estimation of Fuzzy Controller and Its Application to Inverted Pendulum" 17 (17): 37-60, 2004

      8 Swevers, J., "Optimal Robot Excitation and Identification" 13 (13): 730-740, 1997

      9 Daum, F., "Nonlinear Filters : Beyond the Kalman Filter" 20 (20): 57-69, 2005

      10 Orlowska-Kowalska, T., "Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System" 54 (54): 1352-1364, 2007

      11 Villez, K., "Kalman-based Strategies for Fault Detection and Identification(FDI) : Extensions and Critical Evaluation for a Buffer Tank System" 35 (35): 806-816, 2011

      12 Roffel, A. J., "Extended Kalman Filter for Modal Identification of Structures Equipped with a Pendulum Tuned Mass Damper" 333 (333): 6038-6056, 2014

      13 Zheng, M., "Estimation of Rotary Inverted Pendulum by using the Unscented Kalman Filter-Estimation of the Initial State" 1670-1673, 2007

      14 An, C. H., "Estimation of Inertial Parameters of Rigid Body Links of Manipulators" 990-995, 1985

      15 Geetha, M., "Design of State Estimation based Model Predictive Controller for a Two Tank Interacting System" 64 : 244-253, 2013

      16 Mori, S., "Control of Unstable Mechanical System Control of Pendulum" 23 (23): 673-692, 1976

      17 St-Pierre, M., "Comparison between the Unscented Kalman Filter and the Extended Kalman Filter for the Position Estimation Module of an Integrated Navigation Information System" 831-835, 2004

      18 Kim, J., "Comparison between Nonlinear Filtering Techniques for Spiraling Ballistic Missile State Estimation" 48 (48): 313-328, 2012

      19 Bharath Kumar, C., "An Investigation of Extended Kalman Filter and Design of a Model Predictive Controller for Quadruple Tank System" 9 (9): 4255-4261, 2014

      20 Parlos, A. G., "An Algorithmic Approach to Adaptive State Filtering using Recurrent Neural Networks" 12 (12): 1411-1432, 2001

      21 Parlos, A. G., "An Adaptive State Filtering Algorithm for Systems with Partially Known Dynamics" 124 (124): 364-374, 2002

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      2005-05-30 학술지명변경 한글명 : International Journal of the Korean of Precision Engineering -> International Journal of Precision Engineering and Manufacturing
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