Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

Durán, J. Carlos; Escareño, Juan; Etcheverry, Gibran; Rakotondrabe, Micky

doi:10.3390/act5020014

Cited by 9 publications

(5 citation statements)

References 62 publications

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“…0) = 0 &V(x) < 0, ∀x = 0, . Therefore, if the normalized error is defined as E = X re f − X, then a Lyapunov function is defined as Equation (9).…”

Section: Flc Stability Proofmentioning

confidence: 99%

“…Piezoelectric actuators (PEAs) are derived from this technology, where not only can they provide high-precision at small displacements, but also support high forces in comparison to their size [3]; these properties are advantageous due to the downsizing needed for actuators nowadays [4]. PEAs are also designed and produced in different degrees of freedom (DOF), which depend on the required application [5]; a vast number of uses for these actuators, such as computer components [6], machine tools [7], energy recovery [8], and micro-drones [9], are available. Furthermore, PEAs are also used in medicine, where precision is extremely important for purposes as cell puncture [10], drug delivery systems [11], and needle positioning for complex injections [12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

et al. 2020

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Piezoelectric actuators (PEA) are devices that are used for nano- microdisplacement due to their high precision, but one of the major issues is the non-linearity phenomena caused by the hysteresis effect, which diminishes the positioning performance. This study presents a novel control structure in order to reduce the hysteresis effect and increase the PEA performance by using a fuzzy logic control (FLC) combined with a Hammerstein–Wiener (HW) black-box mapping as a feedforward (FF) compensation. In this research, a proportional-integral-derivative (PID) was contrasted with an FLC. From this comparison, the most accurate was taken and tested with a complex structure with HW-FF to verify the accuracy with the increment of complexity. All of the structures were implemented in a dSpace platform to control a commercial Thorlabs PEA. The tests have shown that an FLC combined with HW was the most accurate, since the FF compensate the hysteresis and the FLC reduced the errors; the integral of the absolute error (IAE), the root-mean-square error (RMSE), and relative root-mean-square-error (RRMSE) for this case were reduced by several magnitude orders when compared to the feedback structures. As a conclusion, a complex structure with a novel combination of FLC and HW-FF provided an increment in the accuracy for a high-precision PEA.

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“…0) = 0 &V(x) < 0, ∀x = 0, . Therefore, if the normalized error is defined as E = X re f − X, then a Lyapunov function is defined as Equation (9).…”

Section: Flc Stability Proofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

et al. 2020

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show abstract

“…The combination of smart materials, specifically piezoelectric ones, with algorithms aims to leverage the unique strengths of both tools for enhanced performance in SHM. Additionally, the technologies and processes used to produce these active materials with integrated functionalities continue to gain interest among researchers and industrial players [17][18][19][20][21]. Thanks to the existence of thin film piezoelectric materials, integration is facilitated with minimal mechanical impacts on the structure, all while boasting enhanced sensing capabilities.…”

Section: Introductionmentioning

confidence: 99%

Integration Technology with Thin Films Co-Fabricated in Laminated Composite Structures for Defect Detection and Damage Monitoring

Langat,

De Luycker,

Cantarel

et al. 2024

Micromachines

Self Cite

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Despite the well-established nature of non-destructive testing (NDT) technologies, autonomous monitoring systems are still in high demand. The solution lies in harnessing the potential of intelligent structures, particularly in industries like aeronautics. Substantial downtime occurs due to routine maintenance, leading to lost revenue when aircraft are grounded for inspection and repairs. This article explores an innovative approach using intelligent materials to enhance condition-based maintenance, ultimately cutting life-cycle costs. The study emphasizes a paradigm shift toward structural health monitoring (SHM), utilizing embedded sensors for real-time monitoring. Active thin film piezoelectric materials are proposed for their integration into composite structures. The work evaluates passive sensing through acoustic emission (AE) signals and active sensing using Lamb wave propagation, presenting amplitude-based and frequency domain approaches for damage detection. A comprehensive signal processing approach is presented, and the damage index and damage size correlation function are introduced to enable continuous monitoring due to their sensitivity to changes in material properties and defect severity. Additionally, finite element modeling and experimental validation are proposed to enhance their understanding and applicability. This research contributes to developing more efficient and cost-effective aircraft maintenance approaches through SHM, addressing the competitive demands of the aeronautic industry.

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“…Due to these benefits, PEAs may be used at a vast number of applications such as energy recovery [ 4 ], computer components [ 5 ], motor design [ 6 ], machine tools [ 7 ], and micro-drones [ 8 ]. Furthermore, in the last few years, PEAs have been the subject of study for several medical uses, such as needle positioning for complex injections [ 9 ], micro grippers [ 10 ], and drug delivery systems [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Ultraprecise Controller for Piezoelectric Actuators Based on Deep Learning and Model Predictive Control

Uralde

Artetxe

Barambones

et al. 2023

Sensors

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Piezoelectric actuators (PEA) are high-precision devices used in applications requiring micrometric displacements. However, PEAs present non-linearity phenomena that introduce drawbacks at high precision applications. One of these phenomena is hysteresis, which considerably reduces their performance. The introduction of appropriate control strategies may improve the accuracy of the PEAs. This paper presents a high precision control scheme to be used at PEAs based on the model-based predictive control (MPC) scheme. In this work, the model used to feed the MPC controller has been achieved by means of artificial neural networks (ANN). This approach simplifies the obtaining of the model, since the achievement of a precise mathematical model that reproduces the dynamics of the PEA is a complex task. The presented approach has been embedded over the dSPACE control platform and has been tested over a commercial PEA, supplied by Thorlabs, conducting experiments to demonstrate improvements of the MPC. In addition, the results of the MPC controller have been compared with a proportional-integral-derivative (PID) controller. The experimental results show that the MPC control strategy achieves higher accuracy at high precision PEA applications such as tracking periodic reference signals and sudden reference change.

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Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

Cited by 9 publications

References 62 publications

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

Integration Technology with Thin Films Co-Fabricated in Laminated Composite Structures for Defect Detection and Damage Monitoring

Ultraprecise Controller for Piezoelectric Actuators Based on Deep Learning and Model Predictive Control

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