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- W2990359719 abstract "This thesis discusses the decentralized iterative learning control problem for general interconnected discrete-time systems, which are interlinked by non-affine nonlinear dynamics. And each subsystem does not have direct transmission from input to output. That is to say, each system is irregular. According to the structural characteristics of the system, a D-type learning algorithm is constructed. Using the iterative converge principle, it is shown that the output tracking error of each subsystem can converge to zero along the iteration axis. The effectiveness of the algorithm is verified by simulation." @default.
- W2990359719 created "2019-12-05" @default.
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- W2990359719 date "2019-05-01" @default.
- W2990359719 modified "2023-09-24" @default.
- W2990359719 title "Decentralized Control for Large-Scale Irregular Systems via Iterative Learning Algorithm" @default.
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- W2990359719 doi "https://doi.org/10.1109/ddcls.2019.8908841" @default.
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