| 一种基于模糊CMAC自学习模糊逻辑系统及其在控制中的应用 |
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| 引用本文： | 段培永,张玫,邵惠鹤. 一种基于模糊CMAC自学习模糊逻辑系统及其在控制中的应用[J]. 上海交通大学学报, 2002, 36(4): 543-546 |
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| 作者姓名： | 段培永 张玫 邵惠鹤 |
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| 作者单位： | 1. 山东建筑工程学院,信息与电气工程系,济南,250014
2. 上海交通大学,自动化系,上海,200030 |
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| 摘 要： | 把HCMA（Hyperball Cerebellar Model Articulation Conroller)与模糊逻辑理论有机结合起来，形成FHCMAC（Fuzzy HCMAC)，它便于从输入输出数据中提取模糊规则，直接用作控制器。可以将FHCMAC看作用基函数网络实现的模糊逻辑系统，兼有HCMAC神经网络和模糊逻辑两者的优点，即可以较容易表达定性或模糊的经验知识，又具有很好的学习性能，应用仿真实例验证了其有效性，该方法可应用于难以获取模糊规则的吻合。
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| 关 键 词： | 小脑模型 模糊神经网络 FHCMAC 模糊控制 自学习 模糊逻辑系统 |
| 文章编号： | 1006-2467(2002)04-0543-04 |
| 修稿时间： | 2001-04-29 |
CMAC Based Self-Learning Fuzzy Logical System and Its Application to Automatic Control |
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| DUAN Pei yong ,ZHANG Mei ,SHAO Hui he. CMAC Based Self-Learning Fuzzy Logical System and Its Application to Automatic Control[J]. Journal of Shanghai Jiaotong University, 2002, 36(4): 543-546 |
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| Authors: | DUAN Pei yong ZHANG Mei SHAO Hui he |
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| Affiliation: | DUAN Pei yong 1,ZHANG Mei 1,SHAO Hui he 2 |
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| Abstract: | Combining hyperball cerebellar model articulation controller (HCMAC) with fuzzy logic theories, a fuzzy HCMAC (FHCMAC) was obtained, which can extract fuzzy rules for neurocontrol and be used as a controller directly. The controller is of powerful robustness. The FHCMAC can be regarded as a fuzzy logical system implemented by a basis neural network. It has the advantage of CMAC and fuzzy logic systems, namely, on one hand, FCMAC can express qualitative or fuzzy knowledge easily; on the other hand, it has perfect learning ability. The simulation example confirms the advantages. The presented method can be used to extract logic rules from input output data. |
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| Keywords: | cerebellar model articulation controller (CMAC) self learning fuzzy neural networks fuzzy logical system |
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