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
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.
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.
Jing Chen, Bin Jiang*, and Juan Li
Nanjing University of Aeronautics and Astronautics
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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