| 引用本文: | 陈善本，吴林，张铨，张福恩.具有时滞的不确定性系统神经网络模糊自学习控制[J].控制理论与应用,1996,13(3):347~355.[点击复制] |
| CHEN Shanben and WULin，ZHANG Quan and ZHANG Fuen.A Self-Learning Neural Networks Fuzzy Control of Uncertain Systems with Time Lag[J].Control Theory and Technology,1996,13(3):347~355.[点击复制] |
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| 具有时滞的不确定性系统神经网络模糊自学习控制 |
| A Self-Learning Neural Networks Fuzzy Control of Uncertain Systems with Time Lag |
| 摘要点击 932 全文点击 389 投稿时间：1995-01-21 修订日期：1995-10-16 |
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| DOI编号 |
| 1996,13(3):347-355 |
| 中文关键词 不确定对象 时滞补偿 神经网络 模糊控制 |
| 英文关键词 Uncertain objects time lag compensation neural networks self-learning fuzzy control |
| 基金项目 |
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| 中文摘要 |
| 本文对具有时滞的不确定性控制对象提出了一种神经网络时滞补偿模糊自学习控制方法．模糊控制器采用误差、误差变化及误差加速度的加权和的解析描述形式，利用人工神经网络直接对过程建模，实现对时滞补偿预报以及对模糊加权因子的自学习优化调整．将上述方法用于焊接熔池动态过程控制试验，结果表明本文提出的自学习神经网络时滞补偿模糊控制方案有效． |
| 英文摘要 |
| A self-learning neural network time lag compensation and fuzzy control approach to the controlled uncertain objects with time lag is presented in this paper. Using artificial neural networks for modelling the objects，the fuzzy controller described in the analysis formula with control error，error change and error accelation is real- timely regulated by self-learning weight factors and the time lag compensation and prediction of the systems is realized. The results of experiment on the dynamic Process of weld pool in the pulse TIG welding show that the self-learning neural network time lag compensation and fuzzy control scheme presented in this paper is effective. |