The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
A survey on iterative learning control for nonlinear systems
Abstract
In this article we review the recent advances in iterative learning control (ILC) for nonlinear dynamic systems. In the research field of ILC, two categories of system nonlinearities are considered, namely, the global Lipschitz continuous (GLC) functions and local Lipschitz continuous (LLC) functions. ILC for GLC systems is widely studied and analysed using contraction mapping approach, and the focus of recent exploration moves to application problems, though a number of theoretical issues remain open. ILC for LLC systems is currently a hot area and the recent research focuses on ILC design and analysis by means of Lyapunov approach. The objectives of this article are to introduce recent development and advances in nonlinear ILC schemes, highlight their effectiveness and limitations, as well as discuss the directions for further exploration of nonlinear ILC.
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Slotine, J.-J. E., & Li, W. (1991) · CERN Document Server (European Organization for Nuclear Research) · Cited by 18,975
Adaptive filtering, prediction and control
Ioannou, P. (1985) · Automatica · doi:10.1016/0005-1098(85)90014-7 · Cited by 4,480
On the approximate realization of continuous mappings by neural networks
Funahashi, K.-I. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90003-8 · Cited by 4,206
Adaptive Fuzzy Systems and Control: Design and Stability Analysis
Wang, L.-X. (1994) · Medical Entomology and Zoology · Cited by 3,535
Bettering operation of Robots by learning
Arimoto, S., Kawamura, S., & Miyazaki, F. (1984) · Journal of Robotic Systems · doi:10.1002/rob.4620010203 · Cited by 3,474
Adaptive filtering prediction and control
Goodwin, G. C., & Sin, K. S. (1984) · Cited by 3,400
Computer controlled systems theory and design
(1986) · Automatica · doi:10.1016/0005-1098(86)90095-6 · Cited by 3,003
A survey of iterative learning control
(2006) · IEEE Control Systems · doi:10.1109/mcs.2006.1636313 · Cited by 2,977
Computer-controlled systems: Theory and design
Johnson, C. R. (1985) · Automatica · doi:10.1016/0005-1098(85)90050-0 · Cited by 2,364
Gaussian networks for direct adaptive control
Sanner, R. M., & Slotine, J.-J. E. (1992) · IEEE Transactions on Neural Networks · doi:10.1109/72.165588 · Cited by 2,195
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Data-based techniques focused on modern industry: An overview
Yin, S., Li, X., Gao, H., & Kaynak, O. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2308133 · Cited by 1,025
Metadata
- Authors
- Xu, J.-X.
- Venue
- International Journal of Control
- Publisher
- Informa UK Limited
- Published
- 2011-07
- Volume
- 84
- Issue
- 7
- Pages
- 1275-1294
- ISSN
- 0020-7179 (ISSN-L)
- 1366-5820
- OpenAlex
- W2154529221
- Cited by
- 434
- References
- 23
- FWCI
- 31.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xu, J.-X. (2011). A survey on iterative learning control for nonlinear systems. International Journal of Control. https://doi.org/10.1080/00207179.2011.574236
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