Realization and Comparison of System Identification Based on Different Least Squares Methods

Abstract:

System identification, which includes parameter identification and non-parameter identification, is to estimate its mathematical model based on the input and output observation in system. This paper discusses the system identification theory and establishes a transfer function of 1/4 vehicle’s second-order vibration system model. Through the discrete transfer function, the system’s difference equation can be obtained to identify the system in two ways, RLS (recursive least squares) and RELS (extended recursive least squares). Finally, the paper makes a comparative analysis about RLS and RELS in connection with the vehicle model. The results show that RELS method is more accurate and has stronger convergence than RLS method, which provides the basis for the researching of control system’s algorithm, simulation and making control strategy.

• Periodical: Applied Mechanics and Materials (Volumes 226-228)
• Pages: 2167-2170
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.226-228.2167
• Online since: November 2012
• Authors: Xu Dong Zhang, Ji Fu Guan, Liang Gu
• Keywords: MATLAB, Parameter Identification, Recursive Least Square (RLS), RELS, System Identification

References

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