The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Iterative learning control for discrete-time systems with exponential rate of convergence
Abstract
An algorithm for iterative learning control is proposed based on an optimisation principle used by other authors to derive gradient-type algorithms. The new algorithm is a descent algorithm and has potential benefits which include realisation in terms of Riccati feedback and feedforward components. This realisation also has the advantage of implicitly ensuring automatic step-size selection and hence guaranteeing convergence without the need for empirical choice of parameters. The algorithm achieves a geometric rate of convergence for invertible plants. One important feature of the proposed algorithm is the dependence of the speed of convergence on weight parameters appearing in the norms of the signals chosen for the optimisation problem.
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Citations
Cites
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411
Kailath, T. (1980) · Cited by 6,215
Optimization by Vector Space Methods
(1970) · Students Quarterly Journal · doi:10.1049/sqj.1970.0088 · Cited by 6,004
Lewis, F. L. (1986) · Cited by 2,948
Inversion of multivariable linear systems
Silverman, L. (1969) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1969.1099169 · Cited by 813
Singular Optimal Control Problems
(1975) · Mathematics in Science and Engineering/Mathematics in science and engineering · doi:10.1016/s0076-5392(08)x6179-x · Cited by 363
Iterative learning control using optimal feedback and feedforward actions
AMANN, N., OWENS, D. H., & ROGERS, E. (1996) · International Journal of Control · doi:10.1080/00207179608921697 · Cited by 317
Self-citationTwo-dimensional model and algorithm analysis for a class of iterative learning control systems
Geng, Z., CARROLL, R., & XIE, J. (1990) · International Journal of Control · doi:10.1080/00207179008953571 · Cited by 135
Cited by
An adaptive iterative learning control algorithm with experiments on an industrial robot
Norrlof, M. (2002) · IEEE Transactions on Robotics and Automation · doi:10.1109/tra.2002.999653 · Cited by 264
Metadata
- Authors
- Amann, N., Owens, D. H., & Rogers, E.
- Venue
- IEE Proceedings - Control Theory and Applications
- Published
- 1996-03-25
- Volume
- 143
- Issue
- 2
- Pages
- 217-224
- ISSN
- 1350-2379 (ISSN-L)
- 1359-7035
- OpenAlex
- W2063498039
- Cited by
- 406
- References
- 9
- FWCI
- 7.84
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
