| 压电智能结构模糊自学习控制(FSLC) |
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| 引用本文： | 钱锋,王建国,逄焕平,张鸣祥. 压电智能结构模糊自学习控制(FSLC)[J]. 计算力学学报, 2012, 29(6): 861-866 |
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| 作者姓名： | 钱锋 王建国 逄焕平 张鸣祥 |
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| 作者单位： | 1. 合肥工业大学土木与水利工程学院,合肥,230009
2. 合肥工业大学交通运输工程学院,合肥,230009 |
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| 基金项目： | 国家自然科学基金(11172087);中央高校基本科研业务费专项资金(2011HGBZ1311)资助项目. |
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| 摘 要： | 将模糊逻辑与学习控制的基本思想相结合，根据控制系统的动态输出特性，采用模糊控制对学习控制律中的参数进行实时校正，实现系统的动态学习过程，提出了一种适用于压电智能结构振动控制的模糊自学控制方法FSLC（FuzzySelf-LearningContr01）。分别采用三维8节点实体单元（Solid45）和耦合单元模拟主结构和压电致动器／传感器，基于ANSYS参数化语言编写了压电智能结构振动控制分析的有限元程序。通过数值仿真证明了模糊自学习控制方法能有效控制压电结构的振动，并提高了自学习控制的收敛速度和获得了很好的控制效果。
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| 关 键 词： | 压电智能结构 振动控制 模糊控制 学习控制 |
| 收稿时间： | 2011-08-23 |
| 修稿时间： | 2011-12-18 |
Fuzzy self-learning control of piezoelectric smart structure |
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| QIAN Feng,WANG Jian-guo,PANG Huan-ping and ZHANG Ming-xiang. Fuzzy self-learning control of piezoelectric smart structure[J]. Chinese Journal of Computational Mechanics, 2012, 29(6): 861-866 |
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| Authors: | QIAN Feng WANG Jian-guo PANG Huan-ping ZHANG Ming-xiang |
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| Affiliation: | School of Civil Engineering,Hefei University of Technology,Hefei,230009,China;School of Civil Engineering,Hefei University of Technology,Hefei,230009,China;School of Transportation Engineering,Hefei University of Technology,Hefei,230009,China;School of Civil Engineering,Hefei University of Technology,Hefei,230009,China |
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| Abstract: | According to the output characteristics of control system,a fuzzy controller is used to correct the control law of learning controller in real-time to achieve the dynamic learning process.A fuzzy self-learning control (FSLC) algorithm for piezoelectric smart structure vibration control is presented by the combination of fuzzy logic control and learning control.Piezoelectric actuator/sensor and host structure are modeled by the three-dimension eight-node coupled element (Solid5) and solid element (Solid45) respectively.The finite element program for piezoelectric smart structure vibration control analysis has been compiled by ANSYS parameter language.It is proved that the fuzzy self-learning control (FSLC) method can effectively control the vibration of piezoelectric smart structures by numerical simulation,and speed up the convergence of self-learning control.The fuzzy self-learning control has better control results. |
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| Keywords: | piezoelectric smart structure vibration control fuzzy control learning control |
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