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

• Published in: International journal of control, automation, and systems Vol. 16; no. 1; pp. 150 - 157
• Main Authors: Chen, Jing, Jiang, Bin, Li, Juan
• Format: Journal Article
• Language: English
• Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.02.2018; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Algorithms; Computer simulation; Control; Engineering; Estimating techniques; Finite difference method; Least squares; Mathematical models; Mechatronics; Parameter estimation; Parameter identification; Regular Papers; Robotics; 제어계측공학; parameter estimation; missing output identification model; recursive least squares; Distributed parameter system; finite difference method
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-016-0606-5

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.