Vibration control of smart structures by using neural networks

S. M. Yang, G. S. Lee

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

Smart structure with build-in sensor(s) and actuator(s) that can actively and adoptively change its physical geometry and properties has been considered one of the best candidates in vibration control applications. Implementation of neural networks to system identification and vibration suppression of a smart structure is conducted in this paper. Three neural networks are developed, one for system identification, the second for on-line state estimation, and the third for vibration suppression. It is shown both in analysis and in experiment that these neural networks can identify, estimate, and suppress the vibration of a composite structure by the embedded piezoelectric sensor and actuator. The controller is also shown to be robust to system parameter variations.

Original languageEnglish
Pages (from-to)34-39
Number of pages6
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume119
Issue number1
DOIs
Publication statusPublished - 1997 Mar

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

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