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Active Vibration Control of Composite Cantilever Beams
by
Wang, Xingguo
, Chu, Fulei
, Huang, Zhicheng
, Huang, Fan
in
Active control
/ Algorithms
/ Cantilever beams
/ Control algorithms
/ Control systems
/ Control theory
/ Controllers
/ Cost control
/ Deformation
/ Excitation
/ Feedback
/ Finite element method
/ Genetic algorithms
/ Linear quadratic regulator
/ Mathematical optimization
/ Optimization
/ Particle swarm optimization
/ Piezoelectricity
/ Reduced order models
/ Shear strain
/ System dynamics
/ Vibration
/ Vibration control
/ Vibration damping
/ Viscoelasticity
2022
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Active Vibration Control of Composite Cantilever Beams
by
Wang, Xingguo
, Chu, Fulei
, Huang, Zhicheng
, Huang, Fan
in
Active control
/ Algorithms
/ Cantilever beams
/ Control algorithms
/ Control systems
/ Control theory
/ Controllers
/ Cost control
/ Deformation
/ Excitation
/ Feedback
/ Finite element method
/ Genetic algorithms
/ Linear quadratic regulator
/ Mathematical optimization
/ Optimization
/ Particle swarm optimization
/ Piezoelectricity
/ Reduced order models
/ Shear strain
/ System dynamics
/ Vibration
/ Vibration control
/ Vibration damping
/ Viscoelasticity
2022
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Do you wish to request the book?
Active Vibration Control of Composite Cantilever Beams
by
Wang, Xingguo
, Chu, Fulei
, Huang, Zhicheng
, Huang, Fan
in
Active control
/ Algorithms
/ Cantilever beams
/ Control algorithms
/ Control systems
/ Control theory
/ Controllers
/ Cost control
/ Deformation
/ Excitation
/ Feedback
/ Finite element method
/ Genetic algorithms
/ Linear quadratic regulator
/ Mathematical optimization
/ Optimization
/ Particle swarm optimization
/ Piezoelectricity
/ Reduced order models
/ Shear strain
/ System dynamics
/ Vibration
/ Vibration control
/ Vibration damping
/ Viscoelasticity
2022
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Journal Article
Active Vibration Control of Composite Cantilever Beams
2022
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Overview
This paper deals with the active vibration control of composite cantilever beam. Based on the finite element method and Golla–Hughes–McTavish (GHM) model, the system dynamics equation is established. Models are simplified in physical and modal space because of unobservable and uncontrollable. Based on the particle swarm optimization (PSO) algorithm, the linear quadratic regulator (LQR) feedback gain was optimized. The effect of system vibration damping under different controller parameters, piezoelectric-constrained layer position and excitation signal was studied. The study show that the optimal feedback gain of the controller can effectively balance the control effect and the control cost. The closer the piezoelectric layer and viscoelastic layer are to the fixed end, the better the system control effect and the smaller the control cost. The reduced-order model has a good control effect on different excitation signals.
Publisher
MDPI AG,MDPI
Subject
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