Motion Control, Mechatronics Design, and Moore's Law

Steinbuch, M Maarten; Oomen, Tom; Vermeulen, Hans

doi:10.1541/ieejjia.21006010

Cited by 23 publications

(9 citation statements)

References 42 publications

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“…Over the past few decades, the information-technology market has grown rapidly, largely because the performance of computing systems has improved significantly over time due to Moore’s law [ 1 , 2 , 3 , 4 ]. Big-data processing is considered a new benchmark in addition to performance, which is of great importance in applications such as the Internet of Things (IoT), autonomous vehicles, and adaptive control and management systems [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Nanoscale-Resistive Switching in Forming-Free Zinc Oxide Memristive Structures

et al. 2022

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This article presents the results of experimental studies of the impact of electrode material and the effect of nanoscale film thickness on the resistive switching in forming-free nanocrystalline ZnO films grown by pulsed laser deposition. It was demonstrated that the nanocrystalline ZnO film with TiN, Pt, ZnO:In, and ZnO:Pd bottom electrodes exhibits a nonlinear bipolar effect of forming-free resistive switching. The sample with Pt showed the highest resistance values RHRS and RLRS and the highest value of Uset = 2.7 ± 0.4 V. The samples with the ZnO:In and ZnO:Pd bottom electrode showed the lowest Uset and Ures values. An increase in the number of laser pulses from 1000 to 5000 was shown to lead to an increase in the thickness of the nanocrystalline ZnO film from 7.2 ± 2.5 nm to 53.6 ± 18.3 nm. The dependence of electrophysical parameters (electron concentration, electron mobility, and resistivity) on the thickness of the forming-free nanocrystalline ZnO film for the TiN/ZnO/W structure was investigated. The endurance test and homogeneity test for TiN/ZnO/W structures were performed. The structure Al2O3/TiN/ZnO/W with a nanocrystalline ZnO thickness 41.2 ± 9.7 nm was shown to be preferable for the manufacture of ReRAM and memristive neuromorphic systems due to the highest value of RHRS/RLRS = 2307.8 ± 166.4 and low values of Uset = 1.9 ± 0.2 V and Ures = −1.3 ± 0.5 V. It was demonstrated that the use of the TiN top electrode in the Al2O3/TiN/ZnO memristor structure allowed for the reduction in Uset and Ures and the increase in the RHRS/RLRS ratio. The results obtained can be used in the manufacturing of resistive-switching nanoscale devices for neuromorphic computing based on the forming-free nanocrystalline ZnO oxide films.

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Section: Introductionmentioning

confidence: 99%

Nanoscale-Resistive Switching in Forming-Free Zinc Oxide Memristive Structures

et al. 2022

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“…Additional information regarding the operational details of these systems can be sourced elsewhere [88]. While piezoelectric microswitches are widely integrated into electronic devices, the incessant pursuit of reducing device size in line with Moore's law [89] poses limitations to their practical application in the future. To address this, a transition from microscale to nanoscale is necessary, ensuring compatibility with nanotechnology and nanoelectronics applications [20,21] piezoelectric nanoswitches, which integrate electrical and mechanical properties on the nanoscale, collectively termed NEMS, a category encompassing nanotechnologies [21,90,91].…”

Section: Piezoelectric Nanoswitch Applicationsmentioning

confidence: 99%

Nano-electro-mechanical conduct of boron nitride nanotube as piezoelectric nanogenerators and nanoswitches

Ertekin

2024

Smart Mater. Struct.

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This study investigates various aspects related to the Internet of Things (IoT) and piezoelectric nanoswitches applications, including the frequency band and set-up of piezoelectric nanogenerators, the electrical-mechanical interactions of nanoswitch arrays and their switching times. To address these issues, the molecular dynamics simulations conducted to investigate the performance of a boron nitride nanotube (BNNT) in piezoelectric nanogenerator and nanoswitch applications. For the piezoelectric nanogenerator, BNNT with a diameter-to-length ratio of 0.09 and subjected to 1% compressing exhibited a bistable configuration with a snap-through activation energy of 0.8 meV and a resonance frequency of 48 GHz. These resonance conditions can be achieved by millimeter-wave frequencies under the U-band (40–60 GHz), resulting in axial polarization of 4 mC.m−2 and axial voltage of 13.4 volts. These results demonstrate the potential of BNNT as a broadband and non-linear piezoelectric nanogenerator. For piezoelectric nanoswitches applications, the BNNT zigzag type with a diameter-to-length ratio of 0.32 and subjected to 2.5% compressing displayed 0.017 C.m−2 axial polarization, 22 V axial voltage, and a rapid switching time of approximately 2.0 ns.

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“…(42) corresponds a two-mass spring damper system widely researched in high precision motion control [4], [29], [30]. The feedback controller is designed according to the loop shaping method and given by C f b = 2.697 × 10 5 q 2 − 5.362 × 10 5 q + 2.665 × 10 5 q 3 − 2.04q 2 + 1.117q − 0.07766…”

Section: ) Simulation Setupmentioning

confidence: 99%

An Adaptive Data-Driven Iterative Feedforward Tuning Approach Based on Fast Recursive Algorithm: With Application to a Linear Motor

Yang

Zanchetta

et al. 2023

IEEE Trans. Ind. Inf.

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The feedforward control can effectively improve the servo performance in applications with high requirements of velocity and acceleration. The iterative feedforward tuning method (IFFT) enables the possibility of both removing the need for prior knowledge of the system plant in model-based feedforward and improving the extrapolation capability for varying tasks of iterative learning control. However, most of IFFT methods require to set the number of basis functions in advance, which is inconvenient to the system design. To tackle this problem, an adaptive data-driven IFFT based on fast recursive algorithm (IFFT-FRA) is developed in this paper. Explicitly, based on FRA the proposed approach can adaptively tune the feedforward structure, which significantly increases the intelligence of the approach. Additionally, a data-based iterative tuning procedure is introduced to achieve the unbiased estimation of parameters optimization in presence of noise. Comparative experiments on a linear motor confirms the effectiveness of the proposed approach.

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Motion Control, Mechatronics Design, and Moore's Law

Cited by 23 publications

References 42 publications

Nanoscale-Resistive Switching in Forming-Free Zinc Oxide Memristive Structures

Nanoscale-Resistive Switching in Forming-Free Zinc Oxide Memristive Structures

Nano-electro-mechanical conduct of boron nitride nanotube as piezoelectric nanogenerators and nanoswitches

An Adaptive Data-Driven Iterative Feedforward Tuning Approach Based on Fast Recursive Algorithm: With Application to a Linear Motor

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