Regular Papers

International Journal of Control, Automation and Systems 2018; 16(1): 150-157

Published online March 2, 2018

https://doi.org/10.1007/s12555-016-0606-5

© The International Journal of Control, Automation, and Systems

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

Jing Chen, Bin Jiang*, and Juan Li

Nanjing University of Aeronautics and Astronautics

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.

Article

Regular Papers

International Journal of Control, Automation and Systems 2018; 16(1): 150-157

Published online February 1, 2018 https://doi.org/10.1007/s12555-016-0606-5

Copyright © The International Journal of Control, Automation, and Systems.

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

Jing Chen, Bin Jiang*, and Juan Li

Nanjing University of Aeronautics and Astronautics

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.

IJCAS
March 2025

Vol. 23, No. 3, pp. 683~972

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