Abstract
This paper presents a novel recursive adaptive integral sliding mode (RAISM) control method based on extended state observer (ESO) for the class of dual-motor nonlinear servo system with unknown backlash. The ESO is utilized to estimate the useful states and predigest the designing course. Then, applying the Chebyshev neural network, the RAISM controller is designed to effectively eliminate the reaching phase and avoid the problem of singularity. The simulation results of comparative experiments verify the validity and higher tracking accuracy of the proposed method.
Original language | English |
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Title of host publication | Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 663-668 |
Number of pages | 6 |
ISBN (Electronic) | 9781509065738 |
DOIs | |
Publication status | Published - 2 Jul 2017 |
Event | 9th International Conference on Modelling, Identification and Control, ICMIC 2017 - Kunming, China Duration: 10 Jul 2017 → 12 Jul 2017 |
Publication series
Name | Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017 |
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Volume | 2018-March |
Conference
Conference | 9th International Conference on Modelling, Identification and Control, ICMIC 2017 |
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Country/Territory | China |
City | Kunming |
Period | 10/07/17 → 12/07/17 |
Keywords
- ESO
- RAISM control method
- dual-motor nonlinear servo system
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Wang, K., Ren, X., Sun, Z., & Zhao, W. (2017). Recursive adaptive integral sliding mode control based on extended state observer for dual-motor servo system. In Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017 (pp. 663-668). (Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017; Vol. 2018-March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMIC.2017.8321538