Abstract
This chapter proposes robust iterative learning control schemes for continuous-time nonlinear systems with various nonparametric uncertainties under nonuniform trial length circumstances. The nonuniform trial length is described by a random variable, which causes a random data missing problem while designing and analyzing algorithms for the precise tracking problem. Three common types of nonparametric uncertainties are taken into account: norm-bounded uncertainty, variation-norm-bounded uncertainty, and norm-bounded uncertainty with unknown coefficients. A novel composite energy function is introduced with the help of a newly defined virtual tracking error for the asymptotical convergence of the proposed schemes. Extensions to multi-input-multi-output cases are also elaborated. Illustrative simulations are provided to verify the theoretical results.
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References
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Shen, D., Li, X. (2019). CEF Techniques for Nonparameterized Nonlinear Continuous-Time Systems. In: Iterative Learning Control for Systems with Iteration-Varying Trial Lengths. Springer, Singapore. https://doi.org/10.1007/978-981-13-6136-4_11
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DOI: https://doi.org/10.1007/978-981-13-6136-4_11
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Print ISBN: 978-981-13-6135-7
Online ISBN: 978-981-13-6136-4
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