Neural network based terminal iterative learning control for uncertain nonlinear non‐affine systems

DOI10.1002/acs.2533zbMath1330.93122OpenAlexW1930285975MaRDI QIDQ5743831

Ronghu Chi, Wang, Danwei, Tianqi Liu

Publication date: 8 February 2016

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2533

zbMATH Keywords

neural networkterminal iterative learning controlnonlinear non-affine systeminitial state variancerun-varying reference

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (1)

Data-driven gradient-based point-to-point iterative learning control for nonlinear systems

Cites Work

• Convergence and robustness of discrete time nonlinear systems with iterative learning control
• Terminal iterative learning control with an application to RTPCVD thickness control
• Nonlinear black-box modeling in system identification: A unified overview
• Adaptive ILC for a class of discrete-time systems with iteration-varying trajectory and random initial condition
• Terminal iterative learning control based station stop control of a train
• An iterative learning controller with initial state learning
• Synthesis of robust multivariable iterative learning controllers with application to a wafer stage motion system
• On initial conditions in iterative learning control
• Adaptive output feedback control of nonlinear systems using neural networks

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