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Takagi–Sugeno Fuzzy Neural Network Hysteresis Modeling for Magnetic Shape Memory Alloy Actuator Based on Modified Bacteria Foraging Algorithm

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Abstract

The magnetic shape memory alloy (MSMA)-based actuator, as a new type of actuator, has a great application prospect in the micro-precision positioning field. However, the input-to-output hysteresis nonlinearity largely hinders its wide application. In this paper, a Takagi–Sugeno fuzzy neural network (TSFNN) model based on the modified bacteria foraging algorithm (MBFA) is innovatively utilized to describe the complex hysteresis nonlinearity of the MSMA-based actuator, and the parameters of TSFNN are optimized by the MBFA. The TSFNN is a combination of the fuzzy-logic system and neural network; thus, it has the capability of approximating the nonlinear mapping function and self-adjustment and is suitable for hysteresis modeling. The MBFA, which can obtain better optimization values, is employed for the parameter identification procedure. To demonstrate the effectiveness of the proposed model, a TSFNN based on the gradient descent algorithm (GDA) is used for comparison. Experimental results clearly show that the proposed modeling method can accurately describe the hysteresis nonlinearity of the MSMA-based actuator and has significance for its future application.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 51675228 and the Program of Science and Technology Development Plan of Jilin Province of China under Grants 20180101052JC, 20190303020SF.

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Authors and Affiliations

  1. Department of Control Science and Engineering, Jilin University, Changchun, 130022, China

    Chen Zhang, Yewei Yu, Yifan Wang & Miaolei Zhou

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  1. Chen Zhang
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  2. Yewei Yu
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  3. Yifan Wang
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  4. Miaolei Zhou
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by [CZ], [YY], and [YW]. The manuscript was written by [CZ] and [MZ]. [MZ], [YY], and [YW] reviewed and edited this manuscript. The funding acquisition and supervision were performed by [MZ]. All authors read and approved the manuscript.

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Correspondence to Miaolei Zhou.

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Zhang, C., Yu, Y., Wang, Y. et al. Takagi–Sugeno Fuzzy Neural Network Hysteresis Modeling for Magnetic Shape Memory Alloy Actuator Based on Modified Bacteria Foraging Algorithm. Int. J. Fuzzy Syst. 22, 1314–1329 (2020). https://doi.org/10.1007/s40815-020-00826-9

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  • DOI: https://doi.org/10.1007/s40815-020-00826-9

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