Abstract
In this paper, an adaptive robust finite-time neural control scheme is proposed for uncertain permanent magnet synchronous motor servo system with nonlinear dead-zone input. According to the differential mean value theorem, the dead zone is represented as a linear time-varying system, and the model uncertainty including the dead zone is approximated by using a simple neural network. Then, an adaptive finite-time controller is designed based on a fast terminal sliding mode control principle, and the singularity problem in the initial TSMC is circumvented by modifying the terminal sliding manifold. Comparative experiments are conducted to validate the effectiveness and superior performance of the proposed method.
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Acknowledgments
The authors would thank the support from the National Natural Science Foundation of China under Grants Nos. 61403343, 61433003 and 61573174, and China Postdoctoral Science Foundation Funded Project under Grant No. 2015M580521.
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Chen, Q., Ren, X., Na, J. et al. Adaptive robust finite-time neural control of uncertain PMSM servo system with nonlinear dead zone. Neural Comput & Applic 28, 3725–3736 (2017). https://doi.org/10.1007/s00521-016-2260-5
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DOI: https://doi.org/10.1007/s00521-016-2260-5