Performance-driven selective high-order stochastic iterative learning control with probabilistic guarantees

Kunhong Chen

doi:10.1016/j.isatra.2026.09.001

Performance-driven selective high-order stochastic iterative learning control with probabilistic guarantees

2026-09-02

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DOI：10.1016/j.isatra.2026.09.001

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Abstract

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• Performance-driven historical error selection guided by probabilistic information. • Conditional test certifies surrogate improvement over P-type update. • Asymptotic convergence preserved with decaying gain.

Keywords:

Stochastic iterative learning control

Probabilistic-information-guided learning

Performance-driven high-order update

Selected iteration

Convergence analysis

Performance-driven selective high-order stochastic iterative learning control with probabilistic guarantees

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