Adaptive ILC algorithms of nonlinear continuous systems with non-parametric uncertainties for non-repetitive trajectory tracking

DOI10.1080/00207721.2014.992493zbMath1345.93093OpenAlexW1987992120MaRDI QIDQ2822275

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Publication date: 30 September 2016

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2014.992493

zbMATH Keywords

nonlinear continuous systemsadaptive iterative learning controlnon-repetitive trajectory trackingnon-parametric uncertainties

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (7)

Data-driven ILC algorithms using AFD in frequency domain for unknown linear discrete-time systems ⋮ <scp>Frequency‐domain‐based</scp> iterative learning control utilizing <scp>n‐</scp>best adaptive Fourier decomposition for nonrepetitive unknown iteration‐independent and iteration‐varying discrete time‐delay systems ⋮ Iterative learning control for non‐repetitive trajectory tracking of robot manipulators with joint position constraints and actuator faults ⋮ Iterative learning control of multivariable uncertain nonlinear systems with nonrepetitive trajectory ⋮ AFD-based ILC designs in frequency domain for linear discrete-time systems ⋮ Adaptive fuzzy ILC of nonlinear discrete-time systems with unknown dead zones and control directions ⋮ Observer-based data-driven iterative learning control

Cites Work

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• An average operator-based PD-type iterative learning control for variable initial state error
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