The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Deadzone compensation in motion control systems using neural networks
Abstract
A compensation scheme is presented for general nonlinear actuator deadzones of unknown width. The compensator uses two neural networks (NN): one to estimate the unknown deadzone, and another to provide adaptive compensation in the feedforward path. The compensator NN has a special augmented form containing extra neurons whose activation functions provide a 'jump function basis set' for approximating piecewise continuous functions. Closed-loop stability analysis for the deadzone compensator is provided, and yield tuning algorithms for the weights of the two NN. The technique provides a general procedure for using NN to determine the pre-inverse of an unknown right-invertible function.
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Cites
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
Cited by
Zhang, T. P., & Ge, S. S. (2007) · Automatica · doi:10.1016/j.automatica.2006.12.014 · Cited by 508
Ni, J., Wu, Z., Liu, L., & Liu, C. (2020) · ISA Transactions · doi:10.1016/j.isatra.2019.07.013 · Cited by 105
Ibrir, S., & Su, C.-Y. (2017) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2016.2597745 · Cited by 19
Metadata
- Authors
- Selmic, R. R., & Lewis, F. L.
- Venue
- Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104)
- Publisher
- IEEE
- Published
- 2002-11-27
- Volume
- 1
- Pages
- 288-292
- ISSN
- 1085-1992 (ISSN-L)
- OpenAlex
- W1565170927
- Cited by
- 327
- References
- 1
- FWCI
- 13.04
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Deadzone compensation in motion control systems using neural networks. https://app.cochat.ai/papers/10.1109/cca.1998.728426
- The paper
- Selmic, R. R., & Lewis, F. L. (2002). Deadzone compensation in motion control systems using neural networks. Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104). https://doi.org/10.1109/cca.1998.728426
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