| 引用本文: | 葛爱冬,王玉振,魏爱荣,刘红波.多变量模糊系统控制设计及其在并行混合电动汽车中的应用(英文)[J].控制理论与应用,2013,30(8):998~1004.[点击复制] |
| GE Ai-dong,WANG Yu-zhen,WEI Ai-rong,LIU Hong-bo.Control design for multi-variable fuzzy systems with application to parallel hybrid electric vehicles[J].Control Theory and Technology,2013,30(8):998~1004.[点击复制] |
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| 多变量模糊系统控制设计及其在并行混合电动汽车中的应用(英文) |
| Control design for multi-variable fuzzy systems with application to parallel hybrid electric vehicles |
| 摘要点击 3012 全文点击 2420 投稿时间：2012-05-09 修订日期：2012-11-16 |
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| DOI编号 10.7641/CTA.2013.12101 |
| 2013,30(8):998-1004 |
| 中文关键词 模糊逻辑控制 最小入度模糊控制 半张量积 |
| 英文关键词 fuzzy logic control least in-degree fuzzy control semi-tensor product |
| 基金项目 This work was supported by the National Natural Science Foundation of China (Nos. G61074068, G61034007, G61174036), and the Research Fund for the Taishan Scholar Project of Shandong Province of China and the Natural Science Foundation of Shandong Province (Nos. ZR2010FM013, ZR2010FM018). |
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| 中文摘要 |
| 利用矩阵半张量积方法研究了多变量模糊系统模糊逻辑控制器的设计, 并得到了若干新的结果. 首先给出了模糊规则新的表示形式, 基于该表示形式, 构造了模糊逻辑控制器的结构矩阵, 将复杂的模糊推理转变成了简单的代数等式. 然后当模糊控制规则不完全时, 建立了最小入度控制算法; 当模糊控制规则不一致时, 给出了相应的处理方法. 最后将得到的结果应用到并行混合电动汽车(PHEV)能量管理和控制策略的模糊控制器设计. |
| 英文摘要 |
| This paper studies the fuzzy logic controller (FLC) design for multi-variable fuzzy systems based on the semi-tensor product of matrices, and presents several new results. A new expression of fuzzy rules for multi-variable FLC is introduced, which is very convenient to use in fuzzy logic inference. Based on the new expression of fuzzy rules, the complex fuzzy reasoning is converted into simple algebraic equations by constructing structural matrices of the FLC. A simulation example is given to demonstrate the effectiveness of the proposed approach. A set of least in-degree controls that remove possible fabricated variables are constructed, and an algorithm is given to design the least in-degree controls when the control rules are incomplete. Principles are proposed for dealing with the inconsistency of fuzzy control rules. Finally, the results obtained in this paper are applied to the design of fuzzy controller for energy management and control strategy of parallel hybrid electric vehicles (PHEV). |