Optimal Shape Control of Piezoelectric Intelligent Structure Based on Genetic Algorithm

Wang, Zhanxi; Qin, Xin; Zhang, Shunqi; Bai, Jing; Li, Jing; Yu, Genjie

doi:10.1155/2017/6702183

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…Wang, Qin [110] introduced a mathematical model focused on shape control of piezoelectric intelligent structures. The study utilizes a genetic algorithm to analyze optimal shape control outcomes for piezoelectric materials in a cantilever plate configuration, where both ends are subjected to specific loads.…”

Section: Mechanical Actuators (Turnbuckles)mentioning

confidence: 99%

A Review: Structural Shape and Stress Control Techniques and their Applications

Manguri,

Saeed,

Jankowski

2024

Arch Computat Methods Eng

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This review article presents prior studies on controlling shape and stress in flexible structures. The study offers a comprehensive survey of literature concerning the adjustment and regulation of shape, stress, or both in structures and emphasizes such control’s importance. The control of systems is classified into three primary classes: nodal movement control, axial force control, and controlling the two classes concurrently. Each class is thoroughly assessed, showcasing diverse methods anticipated by various scholars. Furthermore, the paper discusses methods to reduce the number of devices (actuators) to adjust and optimize actuators’ placement to achieve optimal structural control, considering the cost implications of numerous actuators. Additionally, various actuators are presented in detail, their advantages and disadvantages are also discussed. Moreover, the applications of the presented techniques are reviewed in detail, the essential recommendations for future work are also suggested.

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Section: Mechanical Actuators (Turnbuckles)mentioning

confidence: 99%

A Review: Structural Shape and Stress Control Techniques and their Applications

Manguri,

Saeed,

Jankowski

2024

Arch Computat Methods Eng

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“…In a further study [ 15 ] several optimization techniques were compared (simulated annealing (SA), genetic algorithm (GA), particle swarm optimization (PSO) and TLBO) for the same benchmark problem, finding that the SA method gave better values of the objective function and converged faster. Locations and actuation voltages of a cantilever plate are optimized by genetic algorithm by Wang et al [ 16 ]. The deflections of laminated composite hybrid plate under thermo-electro-mechanical loads were investigated in Gohari et al [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Shape control of moderately thick piezoelectric beams

Schoeftner

2023

Acta Mech

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The present contribution focuses on shape control of thick beam-type structures. First the governing equations of a multi-layered beam are derived by taking advantage of the Timoshenko assumptions and the constitutive relations of piezoelectric materials. The deflection curves are explicitly given for a piezoelectric cantilever subjected to a polynomial distribution of the vertical load and the applied electric voltage. In order to find a solution for the optimal shape control voltage an objective function, which depends on the quadratic deflection curve over the beam length, is minimized. Finally several benchmark examples are given for thick beams and the outcome is compared to finite element results and previously derived shape control results from the scientific literature that hold for thin piezoelectric beams. The presented shape control method shows a better agreement with the numerical outcome than the analytical shape control results within the Bernoulli-Euler theory, but the desired voltage distribution only slightly differs from the outcome for thin beams. Furthermore it is found that for a given total thickness-to-length ratio piezoelectric bimorph structures may be more difficult to be perfectly controlled than three-layer beams with thin piezoelectric layers. This is due to higher order piezoelectric effects which are not considered by the present theory (e.g. the thickness deformation caused by the thickness piezoelectric coupling constant).

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“…Foutsitzi et al 19 extended the work of Hadjigeorgiou et al, 14 and they optimized the electrode potential and distribution of piezoelectric actuators to balance the deformation induced by the external load in clamped-free and clamped-clamped beam. Similarly, Wang et al 20 used GA with the FEM model of cantilever plate to optimize the number of piezoelectric actuators and their voltage for balancing the displacement induced by external load at free end of the cantilever plate. Other FEM-based optimization techniques to calculate the actuator voltage for shape control have been reported elsewhere.…”

Section: Introductionmentioning

confidence: 99%

Finite element method coupled with TLBO for shape control optimization of piezoelectric bimorph in COMSOL Multiphysics

2021

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Finite element methods (FEMs) are more advantageous for analyzing complex geometry and structures than analytical methods. Local search optimization techniques are suitable for the unimodal problem because final result depends on the starting point. On the other hand, to optimize the parameters of multi-minima/maxima problems, global optimization-based FEM is used. Unfortunately, global optimization solvers are not present in, COMSOL Multiphysics, a versatile tool for solving varieties of problems using FEM. Teaching–learning-based optimization (TLBO) is a global optimization technique and does not require any algorithm-specific parameter. In this paper, FEM is coupled with TLBO algorithms in COMSOL Multiphysics for solving the global optimization problem. The TLBO algorithm is implemented in COMSOL Multiphysics using the JAVA application programming interface and tested with the standard benchmark functions. The solutions of the standard benchmark problem in COMSOL Multiphysics are in close agreement with the results presented in literature. Furthermore, the optimization procedure thus established is used for the optimization of actuator voltage for piezoelectric bimorphs to achieve the desired shapes. The FEM-based TLBO method is compared with two optimization methods present in COMSOL Multiphysics for a shape control problem; (i) method of moving asymptotes (MMA) and (ii) Bound Optimization BY Quadratic Approximation (BOBYQA). The root mean square error shows that the FEM-based TLBO algorithm converges to a global minimum and gives the same result (19.3 nm) at multiple runs, whereas MMA and BOBYQA trapped in local minimum and gave different results for different starting points.

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Optimal Shape Control of Piezoelectric Intelligent Structure Based on Genetic Algorithm

Cited by 8 publications

References 16 publications

A Review: Structural Shape and Stress Control Techniques and their Applications

A Review: Structural Shape and Stress Control Techniques and their Applications

Shape control of moderately thick piezoelectric beams

Finite element method coupled with TLBO for shape control optimization of piezoelectric bimorph in COMSOL Multiphysics

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