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The Auxiliary Model Based Hierarchical Estimation Algorithms for Bilinear Stochastic Systems with Colored Noises

  • Control Theory and Applications
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International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

This paper considers the parameter identification for a class of nonlinear stochastic systems with colored noise. An input-output representation is derived by eliminating the state variables in the bilinear system. Based on the obtained identification model, a recursive generalized extend least squares algorithm is proposed by using the auxiliary model identification idea. Moreover, a two-stage recursive generalized extended least squares algorithm is presented to reduce the computational burden by using the hierarchical identification principle and the auxiliary model identification idea, respectively. A stochastic gradient identification algorithm is proposed for comparison. The simulation results show that the proposed algorithms have a good performance in estimating the parameters of the bilinear systems with colored noises.

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Authors and Affiliations

  1. School of Electrical and Mechanical Engineering, Qingdao University of Science and Technology, Qingdao, 266061, P. R. China

    Chunqiu Guo, Longjin Wang & Fang Deng

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  1. Chunqiu Guo
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  2. Longjin Wang
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Correspondence to Longjin Wang.

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Recommended by Associate Editor Chang Kyung Ryoo under the direction of Editor Young IL Lee. This work was supported by the National Natural Science Foundation of China (No. 61803049) and the Natural Science Foundation of Shandong Province (ZR201702170236). The authors are grateful to Professor Feng Ding for his helpful suggestions and the main idea of this work comes from him and his series papers in system identification.

Chunqiu Guo received her B.S. and M.S. degrees, in 2007 and 2010, respectively. She is currently an engineer of Qing-dao University of Science and Technology. Her research interests include mathematical statistics and system identification.

Longjin Wang received his Ph.D. degree in Control Science and Engineering from Harbin Engineering University, Harbin, China, in 2009. From 2009 to 2013, he was an engineer at China Shipbuilding Heavy Industry Corporation. Since 2013, he has been an associate professor in Control Science and Engineering at Qingdao University of Science and Technology. His current research interests include system identification and motion control of marine crafts.

Fang Deng received her B.S. degree in Process Equipment and control engineering from Sichuan University, China, in 2003. She received her M.S. degree in chemical machinery from ZheJiang University in 2006. She is currently working toward a Ph.D. degree at Qingdao University of Science and Technology. Her current research interests include nonlin- ear control and estimation, adaptive control, and application in motion control of marine crafts.

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Guo, C., Wang, L. & Deng, F. The Auxiliary Model Based Hierarchical Estimation Algorithms for Bilinear Stochastic Systems with Colored Noises. Int. J. Control Autom. Syst. 18, 650–660 (2020). https://doi.org/10.1007/s12555-019-0115-4

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