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Joint Estimation of States and Parameters for an Input Nonlinear State-Space System with Colored Noise Using the Filtering Technique

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Abstract

This paper concerns the state and parameter estimation problem for an input nonlinear state-space system with colored noise. By using the data filtering and the over-parameterization technique, we transform the original nonlinear state-space system into two identification models with filtered states: one containing the system parameters and the other containing the noise model’s parameters. A combined state and parameter estimation algorithm is developed for identifying the state-space system. The key is that the estimation of system parameters uses the estimated states, and the estimation of states uses the preceding parameter estimates. A simulation example is provided to show that the proposed algorithm can work well.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61273194) and the PAPD of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, People’s Republic of China

    Xuehai Wang & Feng Ding

  2. School of Mathematics and Physics, Henan University of Urban Construction, Pingdingshan, 467036, People’s Republic of China

    Xuehai Wang

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  1. Xuehai Wang
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  2. Feng Ding
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Correspondence to Feng Ding.

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Wang, X., Ding, F. Joint Estimation of States and Parameters for an Input Nonlinear State-Space System with Colored Noise Using the Filtering Technique. Circuits Syst Signal Process 35, 481–500 (2016). https://doi.org/10.1007/s00034-015-0071-z

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  • DOI: https://doi.org/10.1007/s00034-015-0071-z

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