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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压电智能结构模糊自学习控制(FSLC) |
Fuzzy self-learning control of piezoelectric smart structure |
投稿时间:2011-08-23 修订日期:2011-12-18 |
DOI:10.7511/jslx20126009 |
中文关键词: 压电智能结构 振动控制 模糊控制 学习控制 |
英文关键词:piezoelectric smart structure vibration control fuzzy control learning control |
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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中文摘要: |
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(Fuzzy Self-Learning Control)。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。 |
英文摘要: |
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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