Active Vibration Control of a Doubly Curved Composite Shell Stiffened by Beams Bonded with Discrete Macro Fibre Composite Sensor/Actuator Pairs

Ali H. Daraji, Jack M. Hale, Jianqiao Ye

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Abstract

Doubly curved stiffened shells are essential parts of many large-scale engineering structures, such as aerospace, automotive and marine structures. Optimization of active vibration reduction has not been properly investigated for this important group of structures. This study develops a placement methodology for such structures under motion base and external force excitations to optimize the locations of discrete piezoelectric sensor/actuator pairs and feedback gain using genetic algorithms for active vibration control. In this study, fitness and objective functions are proposed based on the maximization of sensor output voltage to optimize the locations of discrete sensors collected with actuators to attenuate several vibrations modes. The optimal control feedback gain is determined then based on the minimization of the linear quadratic index. A doubly curved composite shell stiffened by beams and bonded with discrete piezoelectric sensor/actuator pairs is modeled in this paper by first-order shear deformation theory using finite element method and Hamilton's principle. The proposed methodology is implemented first to investigate a cantilever composite shell to optimize four sensor/actuator pairs to attenuate the first six modes of vibration. The placement methodology is applied next to study a complex stiffened composite shell to optimize four sensor/actuator pairs to test the methodology effectiveness. The results of optimal sensor/actuator distribution are validated by convergence study in genetic algorithm program, ANSYS package and vibration reduction using optimal linear quadratic control scheme.

Original languageEnglish
Article number121009
Number of pages11
JournalJournal of Dynamic Systems, Measurement and Control
Volume140
Issue number12
DOIs
Publication statusPublished - 23 Jul 2018

Fingerprint

fiber composites
Vibration control
Macros
Actuators
actuators
vibration
composite materials
Fibers
sensors
Sensors
Composite materials
methodology
genetic algorithms
vibration mode
Genetic algorithms
Ocean structures
optimization
fitness
optimal control
Shear deformation

Keywords

  • base excitation
  • composite
  • genetic algorithms
  • Sensor
  • stiffened shell
  • vibration control

ASJC Scopus subject areas

  • Mechanical Engineering
  • Aerospace Engineering
  • Control and Systems Engineering
  • Automotive Engineering
  • Civil and Structural Engineering

Cite this

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abstract = "Doubly curved stiffened shells are essential parts of many large-scale engineering structures, such as aerospace, automotive and marine structures. Optimization of active vibration reduction has not been properly investigated for this important group of structures. This study develops a placement methodology for such structures under motion base and external force excitations to optimize the locations of discrete piezoelectric sensor/actuator pairs and feedback gain using genetic algorithms for active vibration control. In this study, fitness and objective functions are proposed based on the maximization of sensor output voltage to optimize the locations of discrete sensors collected with actuators to attenuate several vibrations modes. The optimal control feedback gain is determined then based on the minimization of the linear quadratic index. A doubly curved composite shell stiffened by beams and bonded with discrete piezoelectric sensor/actuator pairs is modeled in this paper by first-order shear deformation theory using finite element method and Hamilton's principle. The proposed methodology is implemented first to investigate a cantilever composite shell to optimize four sensor/actuator pairs to attenuate the first six modes of vibration. The placement methodology is applied next to study a complex stiffened composite shell to optimize four sensor/actuator pairs to test the methodology effectiveness. The results of optimal sensor/actuator distribution are validated by convergence study in genetic algorithm program, ANSYS package and vibration reduction using optimal linear quadratic control scheme.",
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