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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Evgenij S. Barbin Tamara G. Nesterenko Aleksej N. Koleda Alena A. Talovskaia Ivan V. Kulinich Denis M. Mokhovikov Laboratory of microsystems engineering The Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Laboratory of Radiophotonics V.E. Zuev Institute of Atmospheric Optics of SB RAS Tomsk Russia Laboratory of Radiophotonics The Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Laboratory of Intelligent Computer Systems V.E. Zuev Institute of Atmospheric Optics of SB RAS Tomsk Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The treatise studies a temperature effect on the microoptoelectromechanical (MOEMS) accelerometer with an optical measuring transducer based on evanescent wave coupling. The work investigates the temperature sensitivity of the mechanical part of the accelerometer in a temperature range from minus $65^{\circ} \mathrm{C}$ to plus $125^{\circ} \mathrm{C}$. The temperature alteration induces stresses in the mechanical structure. Maximum mechanical stresses emerging in the structure at a temperature of minus $65^{\circ} \mathrm{C}$ reach 556.61 MPa for the layer of aluminum that can be used for in-package wire bonding. However, these stresses are smaller than the admissible value for aluminum (690 MPa). The maximum stresses in residual layers of the mechanical structure are several times smaller than those in the aluminum layer. At different temperatures, the eigenfrequency of the accelerometer also changes, which alters its mechanical transmission coefficient. The temperature sensitivity of normalized mechanical transmission coefficient per $1^{\circ} \mathrm{C}$ amounts to $0.00012{ }^{\circ} \mathrm{C}^{-1}$. To compensate the temperature effect on the mechanical transmission coefficient, various design schemes can be used and the output signal can be adjusted according to the temperature sensor readings.

关键词： Temperature sensors Temperature measurement Accelerometers Temperature distribution Sensitivity Transducers Aluminum

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Exploring the use of deep learning in task-flexible ILC

arXiv

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arXiv 2023年

作者： Vinjarapu, Anantha Sai Hariharan Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary Asml Veldhoven Netherlands

Growing demands in today's industry results in increasingly stringent performance and throughput specifications. For accurate positioning of high-precision motion systems, feedforward control plays a crucial role. Nonetheless, conventional model-based feedforward approaches are no longer sufficient to satisfy the challenging performance requirements. An attractive method for systems with repetitive motion tasks is iterative learning control (ILC) due to its superior performance. However, for systems with non-repetitive motion tasks, ILC is generally not applicable, despite of some recent promising advances. In this paper, we aim to explore the use of deep learning to address the task flexibility constraint of ILC. For this purpose, a novel Task Analogy based Imitation Learning (TAIL)-ILC approach is developed. To benchmark the performance of the proposed approach, a simulation study is presented which compares the TAIL-ILC to classical model-based feedforward strategies and existing learning-based approaches, such as neural network based feedforward *** Codes 37M15 © 2023, CC BY.

关键词： Feedforward control

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Geometric Parameterized Macromodel of Uniaxial Capacitance Accelerometer Based on Modal Superposition 16

Geometric Parameterized Macromodel of Uniaxial Capacitance A...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering, APEIE 2023

作者： Gridchin, Aleksandr V. Koleda, Aleksei N. Barbin, Evgenii S. Nesterenko, Tamara G. Kolchuzhin, Vladimir A. Department of Semiconductor Devices and Microelectronics Novosibirsk State Technical University Novosibirsk Russia Department of Electronic Engineering National Research Tomsk Polytechnic University Tomsk Russia Laboratory of Intelligent Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Advanced Cellular Group Qorvo Munich GmbH Munich Germany

ISBN: (纸本)9798350330885

The paper presents a piecewise geometric parameterization method and a parametric analysis of uniaxial capacitance accelerometer using a reduced model formulated on the modal superposition method. The extraction of parameters for the macromodel such as modal frequencies, modal masses, modal stiffnesses, strain energy, and capacitances are described. The reduced model consists of the two modes: torsion mode, and transversal mode, three electrodes in the electrostatic domain, and eight master nodes in the geometrical domain located at the edges of the plate. The generation of the discrete macromodels is executed using commercial software. The thickness of the plate has been selected as a design parameter. Linear piecewise interpolation is used for macromodel parameterization which have been done inside VHDL-AMS code. The accelerometer's dynamic response simulated using of parametrized macromodel considering the mechanical contact phenomena and the nonlinear electrostatic interaction are presented and discussed. The developed approach can be applied for fast system level simulations in view of the variation of the geometric parameters. © 2023 IEEE.

关键词： Capacitance

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Universal Approximator Approach for Fuzzy Modeling in Thermoelectric Generator 21

Universal Approximator Approach for Fuzzy Modeling in Thermo...

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21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Derbel, Achraf Trigona, Carlo Baccar, Noura Derbel, Nabil Mediterranean Institute of Technology South Mediterranean University Departement of Computer Systems Eng. Tunisia Università Degli Studi di Catania DIEEI Dipartimento di Ingegneria Elettrica Elettronica e Informatica Italy National Engineering School of Sfax University of Sfax Laboratory of Control & Energy Management ENIS Tunisia

ISBN: (纸本)9798350374131

This study explores the application of fuzzy systems as universal approximators for nonlinear functions, focusing on mono-variable and scalable to multi-variable functions. Ensuring error-free approximations through quadratic terms, our method-ology emphasizes reliability. Shifting to practicality, we investi-gate thermoelectric generators' dynamic response to temperature fluctuations. The research underscores fuzzy systems' precision in modeling TEG behavior, validating applicability and accuracy through diverse temperature scenarios. © 2024 IEEE.

关键词： Fuzzy systems

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Numerical Simulation of Grating Input/Output Elements into Optical Waveguides Based on Si3N4/SiO2 Thin Films

Numerical Simulation of Grating Input/Output Elements into O...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Evgenij S. Barbin Ivan V. Kulinich Aleksej N. Koleda Ayan Myrzakhmetov Anton Perin Laboratory of Radiophotonics The Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Laboratory of Intelligent Computer Systems Institute of Optics and Atmosphere Siberian Branch of the Russian Academy of Sciences Tomsk Russia Laboratory of Photonic Integrated Circuits The Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

This paper presents the results of modeling a grating element for input/output of optical radiation into Si 3 N 4 /SiO 2 waveguide structures in the wavelength range from 1.5 to $1.6\ \mu \mathrm{m}$ . The results of the study of the geometric parameters of a diffraction grating on the optical transmission coefficient, in particular: the grating period, undercutting period, etching depth, filling factor, are presented. For a wavelength of $1.55\ \mu \mathrm{m}$ the maximum optical transmission coefficient is observed at: grating period $0.875\ \mu \mathrm{m}$ ; etching depth $0.181\ \mu \mathrm{m}$ ; fill factor of $0.595\ \mu \mathrm{m}$ ; undercutting $\pm 0.015\ \mu \mathrm{m}$ . The greatest contribution to the change in the transmission coefficient is made by the change in the grating period and is $\pm 0.0022\ \mu \mathrm{m}/{\%}$ and the etching depth is $\pm 0.00762\ \mu \mathrm{m}/{\%}$ . Based on the results of simulations, taking into account the operating wavelengths and refractive indices of Si 3 N 4 /SiO 2 films, the following permissible deviations of diffraction lattice parameters were put forward: grating period $\pm 0.022\ \mu \mathrm{m}$ ; etching depth $\pm 0.0762\ \mu \mathrm{m}$ ; filling factor ±20%; undercutting period $\pm 0.14\ \mu \mathrm{m}$ . Permissible insertion angles were 10–12 degrees. The reflection loss at the input of light into the waveguide was −17 dB, and at the output from −20 to −35 dB. Transmission loss at −3dB was $0.09\ \mu \mathrm{m}$ .

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Pedestrian detection with high-resolution event camera

arXiv

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arXiv 2023年

作者： Wzorek, Piotr Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Krakow Poland

Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars still poses many challenges. A video stream captured by traditional cameras is often prone to problems such as motion blur or degraded image quality due to challenging lighting conditions. In addition, the frame rate – typically 30 or 60 frames per second – can be a limiting factor in certain scenarios. Event cameras (DVS – Dynamic Vision Sensor) are a potentially interesting technology to address the above mentioned problems. In this paper, we compare two methods of processing event data by means of deep learning for the task of pedestrian detection. We used a representation in the form of video frames, convolutional neural networks and asynchronous sparse convolutional neural networks. The results obtained illustrate the potential of event cameras and allow the evaluation of the accuracy and efficiency of the methods used for high-resolution (1280 x 720 pixels) footage. © 2023, CC BY.

关键词： Cameras

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Pedestrian detection with high-resolution event camera

TechRxiv

引用

TechRxiv 2023年

作者： Wzorek, Piotr Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Krakow Poland

关键词： Cameras

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computer Vision-control-Based CNN-PID for Mobile Robot

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computers, Materials & Continua 2021年第7期68卷 1065-1079页

作者： Rihem Farkh Mohammad Tabrez Quasim Khaled Al jaloud Saad Alhuwaimel Shams Tabrez Siddiqui College of Engineering Muzahimiyah BranchKing Saud UniversityP.O.Box 2454Riyadh11451Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia King Abdulaziz City for Science and Technology Saudi Arabia Department of Computer Science College of Computer Science and Information TechnologyJazan UniversityJazanSaudi Arabia Department of Electrical Engineering Laboratory for AnalysisConception and Control of SystemsLR-11-ES20National Engineering School of TunisTunis El Manar UniversityTunisTunisia

With the development of artificial intelligence technology,various sectors of industry have *** them,the autonomous vehicle industry has developed considerably,and research on self-driving control systems using artificial intelligence has been extensively *** on the use of image-based deep learning to monitor autonomous driving systems have recently been *** this paper,we propose an advanced control for a serving robot.A serving robot acts as an autonomous line-follower vehicle that can detect and follow the line drawn on the floor and move in specified *** robot should be able to follow the trajectory with speed *** controllers were used simultaneously to achieve *** neural networks(CNNs)are used for target tracking and trajectory prediction,and a proportional-integral-derivative controller is designed for automatic steering and speed *** study makes use of a Raspberry PI,which is responsible for controlling the robot car and performing inference using CNN,based on its current image input.

关键词： Autonomous car pid control deep learning convolutional neural network differential drive system raspberry pi

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Binary Stochastic Flip Optimization for Training Binary Neural Networks

Binary Stochastic Flip Optimization for Training Binary Neur...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Tatsukichi Shibuya Nakamasa Inoue Rei Kawakami Ikuro Sato Department of Computer Science Institute of Science Tokyo Tokyo Japan Department of Systems and Control Engineering Institute of Science Tokyo Tokyo Japan Denso IT Laboratory Tokyo Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

For deploying deep neural networks on edge devices with limited resources, binary neural networks (BNNs) have attracted significant attention, due to their computational and memory efficiency. However, once a neural network is binarized, finetuning it on edge devices becomes challenging because most conventional training algorithms for BNNs are designed for use on centralized servers and require storing real-valued parameters during training. To address this limitation, this paper introduces binary stochastic flip optimization (BinSFO), a novel training algorithm for BNNs. BinSFO employs a parameter update rule based on Boolean operations, eliminating the need to store real-valued parameters and thereby reducing memory requirements and computational overhead. In experiments, we demonstrated the effectiveness and memory efficiency of BinSFO in fine-tuning scenarios on six image classification datasets. BinSFO performed comparably to conventional training algorithms with a 70.7% smaller memory requirement. Code is released at https://***/TatsukichiShibuya/ICASSP2025_BinSFO

关键词： Training Speech coding Memory management Signal processing algorithms Signal processing Classification algorithms Servers Speech processing Optimization Image classification

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Parameter Uncertainty Analysis in Precise Pointing control of Flexible Spacecraft

引用

IFAC-PapersOnLine 2022年第20期55卷 241-246页

作者： János Bezsilla Béla Takarics Bálint Vanek Jian Guo Systems and Control Laboratory ELKH Institute for Computer Science and Control Budapest Hungary Faculty of Aerospace Engineering Delft University of Technology Delft The Netherlands

This article focuses on the validation of a classical PID controller scheme for flexible spacecraft with regards to the effect of parameter uncertainty on system stability and pointing precision. A high-fidelity simulation environment with external disturbances was built in Simulink using a control-oriented model of an Earth-observing satellite with a flexible appendage and on-board microvibration sources in orbit around the planet. Then, a PID control loop was designed with sensor dynamics, time delay behaviour, and a smooth trajectory generator. After declaring the natural frequencies, damping ratio, and rotation angle of the appendage, as well as the propellant tank mass to be uncertain, two worst-case scenarios were identified. Comparing the response of worst-case systems with nominal settings, only a minor drop has been found in the phase margins, with little to no difference in the pointing errors (smaller than ±2 arcsec for both roll and pitch).

关键词： flexible spacecraft nonlinear dynamics attitude tracking precise pointing control PID control parameter uncertainty

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