Abstract
In this paper, we consider several iterative algorithms for Hammerstein systems with hard nonlinearities. The Hammerstein system is first simplified as a polynomial identification model through the key term separation technique, and then the parameters are estimated by using the maximum likelihood (ML) based gradient-based iterative algorithm. Furthermore, an ML least squares auxiliary variable algorithm and an ML bias compensation gradient-based iterative algorithm are developed to identify the saturation system with colored noise. Simulation results are included to illustrate the effectiveness of the proposed algorithms.
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Recommended by Associate Editor Yang Tang under the direction of Editor Hamid Reza Karimi. This work is supported by the National Natural Science Foundation of China (No. 61973137) and the Joint Funds of the National Natural Science Foundation of China (No. U1734210).
Yan Pu received her B.Sc. degree from the School of Mathematical Science, Soo-chow University (Suzhou, China) in 2000, and her M.Sc. degree from the Department of Mathematics, Nanjing University (Nanjing, China) in 2004. She is currently a Ph.D. student at the School of Internet of Things Engineering, Jiangnan University (Wuxi, China). Her research interests include parameter estimation, processing control and system identification.
Yongqing Yang received his B.Sc. degree from Anhui Normal University (Wuhu, China), an M.Sc. degree from Anhui University of Science and Technology (Huainan, China) and a Ph.D. degree from Southeast University (Nanjing, China), in 1985, 1992, and 2007, respectively. He is currently a Professor of Jiangnan University. He is the author or coauthor of more than 50 journal papers. His research interests include nonlinear systems, neural networks and optimization.
Jing Chen received his B.Sc. and M.Sc. degrees from the College of Mathematical Sciences, Yangzhou University (Yangzhou, China), in 2003 and 2006, respectively. He received his Ph.D. degree from the School of Internet of Things Engineering, Jiangnan University (Wuxi, China) in 2013. He is an Assistant Professor at the School of Science, Jiangnan University. His research interests include processing control and system identification.
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Pu, Y., Yang, Y. & Chen, J. Maximum Likelihood Iterative Algorithm for Hammerstein Systems with Hard Nonlinearities. Int. J. Control Autom. Syst. 18, 2879–2889 (2020). https://doi.org/10.1007/s12555-019-0799-5
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DOI: https://doi.org/10.1007/s12555-019-0799-5