Necessary and sufficient condition for convergence of iterative learning algorithm

DOI10.1016/S0005-1098(02)00014-6zbMath1013.93022OpenAlexW2077312524MaRDI QIDQ1614383

R. Smith

Publication date: 5 September 2002

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0005-1098(02)00014-6

zbMATH Keywords

linear time-varying systemsiterative learning controlMIMO controlshift-variant discrete system

Mathematics Subject Classification ID

Design techniques (robust design, computer-aided design, etc.) (93B51) Multivariable systems, multidimensional control systems (93C35) Discrete-time control/observation systems (93C55)

Related Items (6)

Necessary and sufficient stability condition of LTV iterative learning control systems using a 2-D approach ⋮ Disturbance compensation incorporated in predictive control system using a repetitive learning approach ⋮ Nontracking type iterative learning control based on economic model predictive control ⋮ Further results on iterative learning control with convergence conditions for linear time-variant discrete systems ⋮ A Kiefer‐Wolfowitz Algorithm Based Iterative Learning Control for Hammerstein‐Wiener Systems ⋮ Stability and robustness analysis of cyclic pseudo-downsampled iterative learning control

Cites Work

• Iterative learning control for deterministic systems
• Iterative learning control. Convergence, robustness and applications
• Higher-order iterative learning control algorithm
• A discrete iterative learning control for a class of nonlinear time-varying systems
• Non-linear iterative learning by an adaptive Lyapunov technique
• A discrete-time learning control algorithm for a class of linear time-invariant systems
• Iterative learning control synthesis based on 2-D system theory

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