Abstract
Inspired by multi-innovation stochastic gradient identification algorithm, a reconstructed multi-innovation stochastic gradient identification algorithm (RMISG) is presented to estimate the parameters of sandwich systems in this paper. Compared with the traditional multi-innovation stochastic gradient identification algorithm, the RMISG is constructed by using the multistep update principle which solves the multi-innovation length problem and improves the performance of the identification algorithm. To decrease the calculation burden of the RMISG, the key-term separation principle is introduced to deal with the identification model of sandwich systems. Finally, simulation example is given to validate the availability of the proposed estimator.
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Acknowledgements
This paper is supported by the National Natural Science Foundation of China (No. 61433003, 61273150 and 61321002.), and Shandong Natural Science Foundation of China (ZR2017MF048), Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents (2016RCJJ035), Tai’an Science and Technology development program (2017GX0017).
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Li, L., Ren, X., Lv, Y. (2019). Reconstructed Multi-innovation Gradient Algorithm for the Identification of Sandwich Systems. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2018 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 528. Springer, Singapore. https://doi.org/10.1007/978-981-13-2288-4_30
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DOI: https://doi.org/10.1007/978-981-13-2288-4_30
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