The DOI matches its Crossref record.
Robust adaptive control of a class of nonlinear systems with unknown backlash-like hysteresis
Abstract
Deals with adaptive control of a class of nonlinear dynamic systems preceded by unknown backlash-like hysteresis nonlinearities, where the hysteresis is modeled by a differential equation. By exploiting solution properties of the differential equation and combining those properties with adaptive control techniques, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The new control law ensures global stability of the adaptive system and achieves both stabilization and tracking to within a desired precision. Simulations performed on a nonlinear system illustrate and clarify the approach.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Liu, Y.-J., Lu, S., Tong, S., Chen, X., Chen, C. L. P., & Li, D.-J. (2018) · Automatica · doi:10.1016/j.automatica.2017.07.028 · Cited by 655
Zhou, J., Wen, C., & Zhang, Y. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.835398 · Cited by 572
A survey on hysteresis modeling, identification and control
Hassani, V., Tjahjowidodo, T., & Do, T. N. (2014) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2014.04.012 · Cited by 517
Chen, M., & Ge, S. S. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2015.2455053 · Cited by 501
Adaptive Output Control of Nonlinear Systems With Uncertain Dead-Zone Nonlinearity
Zhou, J., Wen, C., & Zhang, Y. (2006) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.864200 · Cited by 425
Metadata
- Authors
- Su, C.-Y., Stepanenko, Y., Svoboda, J., & Leung, T. P.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2000
- Volume
- 45
- Issue
- 12
- Pages
- 2427-2432
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2158036483
- Cited by
- 618
- References
- 0
- FWCI
- 13.52
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Robust adaptive control of a class of nonlinear systems with unknown backlash-like hysteresis. https://app.cochat.ai/papers/10.1109/9.895588
- The paper
- Su, C.-Y., Stepanenko, Y., Svoboda, J., & Leung, T. P. (2000). Robust adaptive control of a class of nonlinear systems with unknown backlash-like hysteresis. IEEE Transactions on Automatic Control. https://doi.org/10.1109/9.895588
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
