제어로봇시스템학회:학술대회논문집

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Nonlinearity-Compensation Extended Kalman Filter for Handling Unexpected Measurement Uncertainty in Process Tomography

  • Kim, Jeong-Hoon (Department of Electrical & Electronic Engineering Cheju National University) ;
  • Ijaz, Umer Zeeshan (Department of Electrical & Electronic Engineering Cheju National University) ;
  • Kim, Bong-Seok (Department of Electrical & Electronic Engineering Cheju National University) ;
  • Kim, Min-Chan (Department of Chemical Engineering Cheju National University) ;
  • Kim, Sin (Department of Nuclear and Energy Engineering Cheju National University) ;
  • Kim, Kyung-Youn (Department of Electrical & Electronic Engineering Cheju National University)
  • Published : 2005.06.02
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Abstract

The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

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