Optimal vibration control of smart composite beams with optimal size and location of piezoelectric sensing and actuation

Zorić, Nemanja D.; Simonović, Aleksandar; Mitrović, Zoran; Stupar, Slobodan

doi:10.1177/1045389x12463465

Cited by 39 publications

(28 citation statements)

References 52 publications

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“…In the present work, as in Zoric et al (2012), the optimization task is defined as finding the position for the piezoelectric actuators where the control action spends less energy in the effort dispended to attenuating structural vibrations. Therefore, a performance index associated to the system controllability is adopted.…”

Section: Lqr Optimal Controlmentioning

confidence: 99%

“…For simplification purposes, the full modal model can be truncated, assuming that the lower frequency modes are the most important in its time response. Introducing a modal displacement variable , the approximate displacement vector can be represented by a modal superposition of the first modes [Zoric et al (2012), Becker et al (2006)], where the value of is stablished taking into account a compromise between the computational effort versus the required model precision. The modal displacement can, therefore, be represented as: (14) where is a vibration modes matrix truncated to modes.…”

Section: Modal Modelmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Placement of Piezoelectric Macro Fiber Composite Patches on Composite Plates for Vibration Suppression

Padoin¹,

Fonseca²,

Perondi³

et al. 2015

Lat. Am. j. solids struct.

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The increasing demand for light structures in important applications highlights the necessity for using advanced methods in their design, as the structural optimization and optimal control. With sensors and actuators integrated through control systems, these structures have the capacity of sensing environment changes, diagnose localized problems, store and process measured data. They are, then, able to take appropriate action to improve the efficiency of the system or to preserve their structural integrity and safety [Cheng et al. (2008)]. Important applications, according to Abstract This work presents a new methodology for the parametric optimization of piezoelectric actuators installed in laminated composite structures, with the objective of controlling structural vibrations. Problem formulation is the optimum location of a Macro Fiber Composite (MFC) actuator patch by means the maximization of the controllability index. The control strategy is based on a Linear Quadratic Regulator (LQR) approach. For the structural analysis, the modeling of the interaction between the MFC and the structure is made taking into account the active material as one of the orthotropic laminate shell layers. The actuation itself is modeled as an initial strain arising from the application of an electric potential which deforms the rest of the structure. Thereby, modeling the electric field and the electromechanical coupling within the actuator is avoided because these effects are considered analytically. Numerical simulations show that the structural model presents good agreement with numerical and experimental results. Furthermore, the results show that optimizing the location of the actuator in the structure helps the control algorithm to reduce induced structural vibration. KeywordsParametric optimization, macro fiber composite, LQR optimal control, laminated composite material. Crawley (1994), are systems that can sense induced vibration and, thus, applying forces to control the amplitudes. Smart structures are applied mainly in the aerospace industry, where they can be found, for instance, in flexible robot manipulators [Zimcik and Yousefi (2003)]. EduardoThe development of methods to design smart structures is a promising research field, fueled by the existing demand for these structures and the great range of possible applications. In the research area of structural design, the topologic and parametric optimization methods contribute efficiently in the design of lighter structures, decreasing costs and the material utilized, evidencing the sustainability aspects of these approaches [Haftka and Gürdal (1991), Bendsøe and Sigmund (2003)].Optimized structures usually present reduced mass and low internal damping. These features induce the occurrence of structural vibrations, which may cause undesirable operational effects, for instance in positioning accuracy. According to Preumont (2002), the use of an active control system integrated by sensors and actuators is crucial in smart structures. This article presents the applicatio...

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Section: Lqr Optimal Controlmentioning

confidence: 99%

Section: Modal Modelmentioning

confidence: 99%

Optimal Placement of Piezoelectric Macro Fiber Composite Patches on Composite Plates for Vibration Suppression

Padoin¹,

Fonseca²,

Perondi³

et al. 2015

Lat. Am. j. solids struct.

View full text Add to dashboard Cite

show abstract

“…To design the vibration control system of piezoelectric smart structures, control strategy need to be considered for the desired control performance. Besides, the locations and sizes of the piezoelectric actuators and sensors also have a great influence on the control performance [44]. The areas of structure at which the mechanical strain is highest are always the best locations of actuators and sensors.…”

Section: Harmonic Excitationmentioning

confidence: 99%

Optimal fuzzy iterative learning control based on artificial bee colony for vibration control of piezoelectric smart structures

Bai¹,

Yang²,

Li³

et al. 2019

J. vibroeng.

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Combining P-type iterative learning (IL) control, fuzzy logic control and artificial bee colony (ABC) algorithm, a new optimal fuzzy IL controller is designed for active vibration control of piezoelectric smart structures. In order to accelerate the learning speed of feedback gain, the fuzzy logic controller is integrated into the ANSYS finite element (FE) models by using APDL (ANSYS Parameter Design Language) approach to adjust adaptively the learning gain of P-type IL control. For improving the performance and robustness of the fuzzy logic controller as well as diminishing human intervention in the operation process, ABC algorithm is used to automatically identify the optimal configurations for values in fuzzy query table, fuzzification parameters and defuzzification parameters, and the main program of ABC algorithm is operated in MATLAB. The active vibration equations are driven from the FE equations for the dynamic response of a linear elastic piezoelectric smart structure. Considering the vibrations generated by various external disturbances, the optimal fuzzy IL controller is numerically investigated for a clamped piezoelectric smart plate. Results demonstrate that the proposed control approach makes the feedback gain has a fast learning speed and performs excellent in vibration suppression. This is demonstrated in the results by comparing the new control approach with the P-type IL control.

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“…Kumar and Narayanan (2008) numerically reveal that, by optimal placement of collocated piezoelectric actuators and sensors, the designed linear quadratic regulator (LQR) optimal controller can achieve effective vibration reduction of the flexible beam, while requiring a smaller control input compared to DVF control. For vibration control of a thin-walled composite beam, Zorić et al (2013) employ the fuzzy optimization strategy to determine the size and the location of piezoelectric actuators and sensors. The particle swarm optimization (PSO) based LQR controller is then designed to maximize the closed-loop damping ratios 6 and minimize the control input.…”

mentioning

confidence: 99%

Quantitative robust linear parameter varying H_∞ vibration control of flexible structures for saving the control energy

Zhang

Scorletti

Ichchou

et al. 2014

Journal of Intelligent Material Systems and Structures

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Quantitative robust linear parameter varying H∞ vibration control of flexible structures for saving the control energy. Abstract In this article, a general and systematical quantitative robust linear parameter varying (LPV) control method is proposed for active vibration control of LPV flexible structures such that a complete set of control objectives can be considered, especially, the reduction of necessarily required control energy. To achieve this goal, phase and gain control policies are employed in LPV H ∞ control designs for suitable selection of weighting functions. The designed parameter-dependent H ∞ controller allows us to explicitly consider the time-varying parameters of the dynamical models for saving the control energy and achieving other control objectives such as the specification of vibration reduction and qualitative robustness properties to both parametric and dynamic uncertainties. Then, various reliable robustness analyses are conducted to quantitatively verify the robustness properties of the closedloop system. The design processes and the effectiveness of the proposed control method are illustrated by active vibration control of a non-collocated piezoelectric cantilever beam excited by an external position-varying forcewhich is the disturbance to be rejected. This plant has typical positiondependent dynamics and is modeled as an LPV system whose time-varying parameter is the actual position of the disturbance. The numerical simulations demonstrate that, compared to the classical H ∞ control and the acceleration feedback control, the proposed control method allows to compute a quantitatively robust parameter (force position) dependent controller whose benefit is to require less control energy and smaller control input, while satisfying the same control objectives in the frequency domain. KeywordsLPV H ∞ control, phase and gain control policies, saving the control energy, parametric and dynamic uncertainties Problem statementSince lightweight components are widely used in practical structures for miniaturization and efficiency, these structures become more flexible and more susceptible to vibrations, which may cause significant noises, harmful

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Optimal vibration control of smart composite beams with optimal size and location of piezoelectric sensing and actuation

Cited by 39 publications

References 52 publications

Optimal Placement of Piezoelectric Macro Fiber Composite Patches on Composite Plates for Vibration Suppression

Optimal Placement of Piezoelectric Macro Fiber Composite Patches on Composite Plates for Vibration Suppression

Optimal fuzzy iterative learning control based on artificial bee colony for vibration control of piezoelectric smart structures

Quantitative robust linear parameter varying H_∞ vibration control of flexible structures for saving the control energy

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