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Titlebook: Iterative Learning Control with Passive Incomplete Information; Algorithms Design an Dong Shen Book 2018 Springer Nature Singapore Pte Ltd.

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樓主: Gullet
31#
發(fā)表于 2025-3-26 23:44:39 | 只看該作者
Two-Side Data Dropout for Linear Stochastic Systems occurring randomly at both the measurement and actuator sides. Data updating in the memory array is arranged in such a way that data at every time instant is updated independently, which allows successive data dropouts along both time and iteration axes. The update mechanisms for both the computed
32#
發(fā)表于 2025-3-27 03:12:21 | 只看該作者
Two-Side Data Dropout for Nonlinear Systemsly at both measurement and actuator sides. Both updating algorithms are proposed for the computed input signal generated by the learning controller and the real input signal fed to the plant. The system output is strictly proved to converge to the desired reference in almost sure sense as the iterat
33#
發(fā)表于 2025-3-27 05:49:02 | 只看該作者
34#
發(fā)表于 2025-3-27 13:16:53 | 只看該作者
Random Iteration-Varying Lengths for Linear Systemsquired on the probability distribution of randomly iteration-varying lengths. The conventional P-type update law is adopted with Arimoto-like gains and causal gains. The convergence both in almost sure and mean square senses is proved by direct math calculations.
35#
發(fā)表于 2025-3-27 15:52:33 | 只看該作者
Random Iteration-Varying Lengths for Nonlinear Systemsdistribution of random iteration length is required prior for controller design. The conventional P-type update law is used with a modified tracking error because of randomly iteration-varying lengths. A novel technical lemma is proposed for the strict convergence analysis in pointwise sense.
36#
發(fā)表于 2025-3-27 18:09:08 | 只看該作者
Iterative Learning Control for Large-Scale Systemsion equation is with noise. Subsystems are nonlinearly connected via the large state vector of the whole system. The possibility of data missing and communication delay is taken into account. It is proved that decentralized ILC designed in this chapter generates the input sequence that converges to
37#
發(fā)表于 2025-3-27 23:18:39 | 只看該作者
38#
發(fā)表于 2025-3-28 05:55:51 | 只看該作者
Dong Shengn pattern framework description, which takes power consumption and time behavior into account. We evaluate the expressiveness of the framework by defining design patterns, which use elaborated power-saving strategies for various hardware components to reduce the overall energy consumption of an emb
39#
發(fā)表于 2025-3-28 07:01:18 | 只看該作者
40#
發(fā)表于 2025-3-28 11:58:45 | 只看該作者
Dong Shenult to implement given programming language levels of variety. This is compounded by the fact that many existing studies do not detail their methodology and tooling, which precludes researchers from creating surveys to enable data analysis on a larger scale. In our paper, we propose a comprehensive
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