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Missing Output Identification Model Based Recursive Least Squares Algorithm for a Distributed Parameter System

  • Jing Chen
  • Bin Jiang
  • Juan Li
Regular Papers Control Theory and Applications
  • 67 Downloads

Abstract

This paper proposes a recursive least squares algorithm for a distributed parameter system with missing observations. By using the finite difference method, the distributed parameter system can be turned into a lumped parameter system. Then a missing output identification model based recursive least squares algorithm is derived to estimate the unknown parameters of the lumped parameter system. Furthermore, the parameters of the distributed parameter system can be computed by the estimated parameters of the lumped parameter system. The simulation results indicate that the proposed method is effective.

Keywords

Distributed parameter system finite difference method missing output identification model parameter estimation recursive least squares 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingP. R. China
  2. 2.College of Mechanical and Electrical EngineeringQingdao Agricultural UniversityQingdaoP. R. China

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