TY - JOUR
T1 - Active vibration control of smart composite plates using optimized self-tuning fuzzy logic controller with optimization of placement, sizing and orientation of PFRC actuators
AU - Zorić, Nemanja D.
AU - Tomović, Aleksandar M.
AU - Obradović, Aleksandar M.
AU - Radulović, Radoslav D.
AU - Petrović, Goran R.
N1 - Funding Information:
This work is supported by the Funder name: Ministry of Science and Technological Development of Republic of Serbia , Grant ID: TR35035 Ministry of Science and Technological Development of Republic of Serbia through Technological Development Project no. 35035 .
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/9/15
Y1 - 2019/9/15
N2 - This paper deals with optimization of the sizing, location and orientation of the piezo-fiber reinforced composite (PFRC) actuators and active vibration control of the smart composite plates using particle-swarm optimized self-tuning fuzzy logic controller. The optimization criteria for optimal sizing, location and orientation of the PFRC actuators is based on the Gramian controllability matrix and the optimization process is performed by involving the limitation of the plates masses increase. Optimal configurations of five PFRC actuators for active vibration control of the first six modes of cantilever symmetric ((90°/0°/90°/0°)S), antisymmetric cross-ply ((90°/0°/90°/0°/90°/0°/90°/0°)) and antisymmetric angle-ply ((45°/-45°/45°/-45°/45°/-45°/45°/-45°)) composite plates are found using the particle swarm optimization. The detailed analysis of influences of the PFRC layer orientation and position (top or bottom side of composite plates), as well as bending-extension coupling of antisymmetric laminates on controllabilities is also performed. The experimental study is performed in order to validate this behavior on controllabilities of antisymmetric laminates. The particle swarm-optimized self-tuning fuzzy logic controller (FLC) adapted for the multiple-input multiple-output (MIMO) control is implemented for active vibration suppression of the plates. The membership functions as well as output matrices are optimized using the particle swarm optimization. The Mamdani and the zero-order Takagi–Sugeno–Kang fuzzy inference methods are employed and their performances are examined and compared. In order to represent the efficiency of the proposed controller, results obtained using the proposed particle swarm optimized self-tuning FLC are compared with the corresponding results in the case of the linear quadratic regulator (LQR) optimal control strategy.
AB - This paper deals with optimization of the sizing, location and orientation of the piezo-fiber reinforced composite (PFRC) actuators and active vibration control of the smart composite plates using particle-swarm optimized self-tuning fuzzy logic controller. The optimization criteria for optimal sizing, location and orientation of the PFRC actuators is based on the Gramian controllability matrix and the optimization process is performed by involving the limitation of the plates masses increase. Optimal configurations of five PFRC actuators for active vibration control of the first six modes of cantilever symmetric ((90°/0°/90°/0°)S), antisymmetric cross-ply ((90°/0°/90°/0°/90°/0°/90°/0°)) and antisymmetric angle-ply ((45°/-45°/45°/-45°/45°/-45°/45°/-45°)) composite plates are found using the particle swarm optimization. The detailed analysis of influences of the PFRC layer orientation and position (top or bottom side of composite plates), as well as bending-extension coupling of antisymmetric laminates on controllabilities is also performed. The experimental study is performed in order to validate this behavior on controllabilities of antisymmetric laminates. The particle swarm-optimized self-tuning fuzzy logic controller (FLC) adapted for the multiple-input multiple-output (MIMO) control is implemented for active vibration suppression of the plates. The membership functions as well as output matrices are optimized using the particle swarm optimization. The Mamdani and the zero-order Takagi–Sugeno–Kang fuzzy inference methods are employed and their performances are examined and compared. In order to represent the efficiency of the proposed controller, results obtained using the proposed particle swarm optimized self-tuning FLC are compared with the corresponding results in the case of the linear quadratic regulator (LQR) optimal control strategy.
KW - Active vibration control
KW - Fuzzy logic control
KW - Particle swarm optimization
KW - PFRC actuator optimization
KW - Smart composite plate
U2 - 10.1016/j.jsv.2019.05.035
DO - 10.1016/j.jsv.2019.05.035
M3 - Article
AN - SCOPUS:85066426029
SN - 0022-460X
VL - 456
SP - 173
EP - 198
JO - Journal of Sound and Vibration
JF - Journal of Sound and Vibration
ER -