针对具有高约束和未知不确定性的非线性系统，采用单神经元隐层增强的自适应深度神经网络跟踪控制器

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS

International Journal of Modelling Identification and Control Pub Date : 2021-01-01 DOI:10.1504/ijmic.2021.10045904

Hampu Ait Abbas

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Adaptive deep neural network tracking controller augmented using only one-neuron hidden layers for nonlinear systems subject to high constraints and unknown uncertainties

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来源期刊

International Journal of Modelling Identification and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.70

自引率

57.10%

发文量

期刊介绍： Most of the research and experiments in the fields of science, engineering, and social studies have spent significant efforts to find rules from various complicated phenomena by observations, recorded data, logic derivations, and so on. The rules are normally summarised as concise and quantitative expressions or “models". “Identification" provides mechanisms to establish the models and “control" provides mechanisms to improve the system (represented by its model) performance. IJMIC is set up to reflect the relevant generic studies in this area.