Fuzzy self-learning control of piezoelectric smart structure

Feng Qian, Jian Guo Wang, Huan Ping Pang, Ming Xiang Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)861-866
Number of pages6
JournalJisuan Lixue Xuebao/Chinese Journal of Computational Mechanics
Issue number6
StatePublished - Dec 2012

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Modeling and Simulation
  • Applied Mathematics


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