Adaptive Iterative Learning Control for Nonlinearly Parameterized Non-Strict Feedback Nonlinear Systems with Full-State Constraints
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications,Energy Engineering and Power Technology,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s40313-023-01060-y.pdf
Reference49 articles.
1. Ahn, H. S., Chen, Y. Q., & Moore, K. L. (2007). Iterative learning control: Brief survey and categorization. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37(6), 1099–1121. https://doi.org/10.1109/TSMCC.2007.905759
2. Bensidhoum, T., & Bouakrif, F. (2020). Adaptive P-type iterative learning radial basis function control for robot manipulators with unknown varying disturbances and unknown input dead zone. International Journal of Robust and Nonlinear Control, 30(10), 4075–4094. https://doi.org/10.1002/rnc.4988
3. Benslimane, H., Boulkroune, A., & Chekireb, H. (2016). Iterative learning control for strict-feedback nonlinear systems with both structured and unstructured uncertainties. Arabian Journal for Science and Engineering, 41(9), 3683–3694. https://doi.org/10.1007/s13369-015-1901-9
4. Benslimane, H., Boulkroune, A., & Chekireb, H. (2017). Adaptive iterative learning control of nonlinearly parameterized pure feedback nonlinear systems. Journal of Control, Automation and Electrical Systems, 28(4), 457–469. https://doi.org/10.1007/s40313-017-0316-0
5. Chen, Q., Shi, H., & Sun, M. (2020). Echo state network-based backstepping adaptive iterative learning control for strict-feedback systems: an error-tracking approach. IEEE Transactions on Cybernetics, 50(7), 3009–3022. https://doi.org/10.1109/TCYB.2019.2931877
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