Abstract
This chapter considers the adaptive iterative learning control (ILC) for continuous-time parametric nonlinear systems with partial structure information under iteration-varying trial length environments. In particular, two types of partial structure information are taken into account. The first type is that the parametric system uncertainty can be separated as a combination of time-invariant and time-varying part. The second type is that the parametric system uncertainty mainly contains time-invariant part, whereas the designed algorithm is expected to deal with certain unknown time-varying uncertainties. A mixing-type adaptive learning scheme and a hybrid-type differential-difference learning scheme are proposed for the two types of partial structure information cases, respectively. The convergence analysis under iteration-varying trial length environments is strictly derived based on a novel composite energy function. Illustrative simulations are provided to verify the effectiveness of the proposed schemes.
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References
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© 2019 Springer Nature Singapore Pte Ltd.
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Shen, D., Li, X. (2019). CEF Techniques for Uncertain Systems with Partial Structure Information. In: Iterative Learning Control for Systems with Iteration-Varying Trial Lengths. Springer, Singapore. https://doi.org/10.1007/978-981-13-6136-4_12
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DOI: https://doi.org/10.1007/978-981-13-6136-4_12
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6135-7
Online ISBN: 978-981-13-6136-4
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