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首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B >Self-learning fuzzy neural networks for control of uncertain systems with time delays
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Self-learning fuzzy neural networks for control of uncertain systems with time delays

机译:具有时滞的不确定系统控制的自学习模糊神经网络

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摘要

We address the problem of control of uncertain systems with time delays. Using the fuzzy logic control and artificial neural network methodologies, we present a self-learning fuzzy neural control scheme for general uncertain processes. In this scheme, a neural network compensator is designed instead of the classical Smith predictor for attenuating the adverse effects of time delays of the uncertain systems. The scheme has been used in control of welding pool dynamics of the arc welding process, and the experiment results show the control scheme available.
机译:我们解决了具有时滞的不确定系统的控制问题。使用模糊逻辑控制和人工神经网络方法,我们提出了一种用于一般不确定过程的自学习模糊神经控制方案。在该方案中,设计了神经网络补偿器代替经典的Smith预测器,以减轻不确定系统的时间延迟的不利影响。该方案已用于电弧焊过程中焊池动力学的控制,实验结果表明该控制方案是可行的。

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