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CEF Techniques for Uncertain Systems with Partial Structure Information

  • Dong ShenEmail author
  • Xuefang Li
Chapter

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.

References

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    Sun M, Wang D (2002) Iterative learning control with initial rectifying action. Automatica 38(7):1177–1182MathSciNetCrossRefGoogle Scholar
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    Xu JX, Yan R (2005) On initial conditions in iterative learning control. IEEE Trans Autom Control 50(9):1349–1354MathSciNetCrossRefGoogle Scholar
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    Zeng C, Shen D, Wang J (2018) Adaptive learning tracking for uncertain systems with partial structure information and varying trial lengths. J Frankl Inst 355(15):7027–7055MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Information Science and TechnologyBeijing University of Chemical TechnologyBeijingChina
  2. 2.Department of Electrical and Electronic EngineeringImperial College LondonLondonUK

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