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Neural network adaptive iterative learning control for strict-feedback unknown delay systems against input saturation
Neural network adaptive iterative learning control (ILC) is developed in this article to treat
strict-feedback nonlinear systems with unknown state delays and input saturation. These …
strict-feedback nonlinear systems with unknown state delays and input saturation. These …
Optimal iterative learning control under varying iteration lengths with input saturation
M You, J Shen, L Li, M Shen - Optimal Control Applications and …, 2025 - Wiley Online Library
This article is concerned with optimized iterative learning control of linear time‐invariant
systems against input saturation and varying iteration length. The varying length is …
systems against input saturation and varying iteration length. The varying length is …
Krzysztof Gałkowski—an obituary
Krzysztof Gałkowski made telling contributions to his areas of research over more than 40
years. He began his research career in circuit theory. Then he moved to multidimensional …
years. He began his research career in circuit theory. Then he moved to multidimensional …
Iterative Learning Control of an Uncertain System with Input Saturation Using the Measurable Output
J Emelianova - 2023 IEEE 11th International Conference on …, 2023 - ieeexplore.ieee.org
The paper considers a linear discrete-time system operating in a repetitive mode to track a
reference trajectory with a given accuracy. The system parameters are incompletely known …
reference trajectory with a given accuracy. The system parameters are incompletely known …