Active neuro-adaptive vibration suppression of a smart beam

Akin O., ŞAHİN M.

SMART STRUCTURES AND SYSTEMS, vol.20, no.6, pp.657-668, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 6
  • Publication Date: 2017
  • Doi Number: 10.12989/sss.2017.20.6.657
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.657-668
  • Keywords: active vibration suppression, system identification, piezoelectricity, linear quadratic regulator, artificial neural network, performance comparison, FEEDBACK-CONTROL, CONTROL STRATEGIES, FLEXIBLE STRUCTURE, ACTUATORS, SYSTEMS
  • Middle East Technical University Affiliated: Yes


In this research, an active vibration suppression of a smart beam having piezoelectric sensor and actuators is investigated by designing separate controllers comprising a linear quadratic regulator and a neural network. Firstly, design of a smart beam which consists of a cantilever aluminum beam with surface bonded piezoelectric patches and a designed mechanism having a micro servomotor with a mass attached arm for obtaining variations in the frequency response function are presented. Secondly, the frequency response functions of the smart beam are investigated experimentally by using different piezoelectric patch combinations and the analytical models of the smart beam around its first resonance frequency region for various servomotor arm angle configurations are obtained. Then, a linear quadratic regulator controller is designed and used to simulate the suppression of free and forced vibrations which are performed both in time and frequency domain. In parallel to simulations, experiments are conducted to observe the closed loop behavior of the smart beam and the results are compared as well. Finally, active vibration suppression of the smart beam is investigated by using a linear controller with a neural network based adaptive element which is designed for the purpose of overcoming the undesired consequences due to variations in the real system.