在基于二阶Adaline网络的广义预测极点配置控制器
TP3; 为了解决实际应用中非线性被控过程的预测控制问题,把神经网络、广义预测控制和极点配置技术融为一体,提出一个新型自适应神经网络广义预测极点配置加权控制器(GPPWC).首先提出非线性被控过程的二阶自适应线性神经元(Adaline)网络模型,然后给出基于二阶Adaline网络的GPPWC.仿真结果表明该方案的有效性....
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| Veröffentlicht in: | 系统仿真学报 2006, Vol.18 (z2), p.937-956 |
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| container_issue | z2 |
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| container_title | 系统仿真学报 |
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| creator | 吕国芳 王敏 段向军 |
| description | TP3; 为了解决实际应用中非线性被控过程的预测控制问题,把神经网络、广义预测控制和极点配置技术融为一体,提出一个新型自适应神经网络广义预测极点配置加权控制器(GPPWC).首先提出非线性被控过程的二阶自适应线性神经元(Adaline)网络模型,然后给出基于二阶Adaline网络的GPPWC.仿真结果表明该方案的有效性. |
| doi_str_mv | 10.3969/j.issn.1004-731X.2006.z2.267 |
| format | Article |
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| ispartof | 系统仿真学报, 2006, Vol.18 (z2), p.937-956 |
| issn | 1004-731X |
| language | chi |
| recordid | cdi_wanfang_journals_xtfzxb2006z2267 |
| source | Alma/SFX Local Collection |
| title | 在基于二阶Adaline网络的广义预测极点配置控制器 |
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