A composite iterative neural network sliding mode control for hybrid reluctance actuator
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11071-024-10145-5.pdf
Reference28 articles.
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3. Fang, Y.-N., Zhou, R., Zhu, L.-M., Zhu, Z.: Equivalent magnetic network-based multiphysics optimization of a normal-stressed millimeter-range nanopositioning stage. IEEE/ASME Trans. Mechatron. 29(2), 1477–1488 (2023)
4. Pechgraber, D., Csencsics, E., Schitter, G.: Resonant rotational reluctance actuator for large range scanning mirrors. IEEE/ASME Trans. Mechatron. 28(6), 3573–3582 (2023)
5. Ito, S., Troppmair, S., Lindner, B., Cigarini, F., Schitter, G.: Long-range fast nanopositioner using nonlinearities of hybrid reluctance actuator for energy efficiency. IEEE Trans. Industr. Electron. 66(4), 3051–3059 (2018)
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