| 引用本文: | 黄道平,朱学峰, 胥布工.自适应神经元非模型多变量优化补偿控制*[J].控制理论与应用,1998,15(3):346~351.[点击复制] |
| HUANG Daoping, ZHU Xuefeng and XU Bugong.Adaptive Neural Non-Model Optimal CompensatingControl for MIMO System[J].Control Theory & Applications,1998,15(3):346~351.[点击复制] |
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| 自适应神经元非模型多变量优化补偿控制* |
| Adaptive Neural Non-Model Optimal CompensatingControl for MIMO System |
| 摘要点击 1525 全文点击 600 投稿时间:1997-03-19 修订日期:1998-01-16 |
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| DOI编号 |
| 1998,15(3):346-351 |
| 中文关键词 自适应神经元优化补偿 多变量系统 神经元网络 非模型控制 |
| 英文关键词 adaptive neural optimal compensating MIMO system, neural networks non-model control |
| 基金项目 |
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| 中文摘要 |
| 根据解耦补偿和优化控制的思想,本文提出了一种完全不依赖于对象模型的自适应神经元多变量优化补偿器模型,给出了神经元权系数的在线学习方法,分析了其工作机理,进一步给出了在某多侧线精馏塔和连续搅拌釜式反应器(CSTR)上的仿真结果. |
| 英文摘要 |
| Based on the principle of the decoupling compensating and optimal control, an adaptive neural optimal compensator independent on object model and the on-line learning method of neuron weights are pre-sented. The principle of the compensator is analysed. Further, the simulation results in a distillation column with multi-outputs and in a CSTR are shown. |