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Real Time Nanoscale Cleaning Phenomenon Observation During Enforcing MHz Wave By Evanescent Field 241

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Real Time Nanoscale Cleaning Phenomenon Observation During E...

241st ECST Meeting

作者： Terayama, Yutaka Khajornrungruang, Panart Suzuki, Keisuke Mori, Ryotaro Hamada, Satomi Wada, Yutaka Hiyama, Hirokuni Mechanical Science and Technology Division Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka iizuka820-8502 Japan Mechanical Science and Technology Division Department of Intelligent and Control Systems Ebara Corporation Ltd. Kanagawa fujisawa144-8510 Japan

ISBN: (纸本)9781607685395

Post-CMP Cleaning phenomenon is considered as the detachment of the nanoparticle from the substrate surface to be cleaned, and the occasional reattachment of the nanoparticle to surface in nanoscale. However, residual contamination on the substrate has been usually inspected only after the cleaning process. Therefore, the cleaning mechanism of nanoparticles has not already clearly known. Hence, we have established dynamically observation of cleaning phenomena near the surface by applying the evanescent light which occurred a few hundred nm from the surface. In this article, detachments of φ30, 50, 70 nm silica particles and the acoustic cavitation effect were observed during enforcing 1.1 MHz waves in 60 frames per second. The main phenomenon was described that some of each silica nanoparticles were randomly intermittently detached from the surface when the cavitation effect repeatedly irregularly occurs and decays near the surface or remained on the surface during enforcing MHz wave. © 2022 ECS - The Electrochemical Society.

关键词： Silica nanoparticles

Parameter fault estimation in distributed heating/cooling systems 22

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Parameter fault estimation in distributed heating/cooling sy...

Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Wijaya Kurniawan Katalin M. Hangos Lorinc Marton Faculty of Computer Science University of Brawijaya Indonesia) and Departement of Electrical Engineering and Information Systems University of Pannonia Hungary Departement of Electrical Engineering and Information Systems University of Pannonia Hungary and Institute for Computer Science and Control Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Romania)

ISBN: (纸本)9781450397117

In this paper, the problem of fault estimation and localization in the connecting dynamic elements of distributed heating and cooling systems are treated. The fault represents the physical parameter change related to the heat transfer between the system and the external environment. First, based on the bi-linear dynamic state space model of the system in the presence of a fault, structural observability analysis using Signed Directed Graph (SDG) has been performed to investigate the sensor placement problem. Then, a nonlinear observer with a parameter adaptation algorithm was proposed for fault estimation. The simulation results show that it can successfully detect and estimate the fault. Fault localization along the length of the element has also been attempted, but it has been found that the localization cannot be performed using practically changeable input variables. Frequency domain analysis is presented to discuss this phenomenon.

关键词： Nonlinear Observer Heating/cooling system Fault diagnosis Structural observability Parameter estimation

CONTINUOUS-TIME IDENTIFICATION OF DYNAMIC STATE-SPACE MODELS BY DEEP SUBSPACE ENCODING

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arXiv 2022年

作者： Beintema, Gerben I. Schoukens, Maarten Tóth, Roland Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time (DT) models. However, even with numerous recent developments, the CT nonlinear state-space (NL-SS) model identification problem remains to be solved in full, considering common experimental aspects such as the presence of external inputs, measurement noise, latent states, and general robustness. This paper presents a novel estimation method that addresses all these aspects and that can obtain state-of-the-art results on multiple benchmarks with compact fully connected neural networks capturing the CT dynamics. The proposed estimation method called the subspace encoder approach (SUBNET) ascertains these results by efficiently approximating the complete simulation loss by evaluating short simulations on subsections of the data, by using an encoder function to estimate the initial state for each subsection and a novel state-derivative normalization to ensure stability and good numerical conditioning of the training process. We prove that the use of subsections increases cost function smoothness together with the necessary requirements for the existence of the encoder function and we show that the proposed state-derivative normalization is essential for reliable estimation of CT NL-SS models. © 2022, CC BY.

关键词： Cost functions

Distributed Online Bandit Nonconvex Optimization with One-Point Residual Feedback via Dynamic Regret

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arXiv 2024年

作者： Hua, Youqing Liu, Shuai Hong, Yiguang Johansson, Karl Henrik Wang, Guangchen School of Control Science and Engineering Shandong University Jinan China Nanyang Technological University Singapore Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper considers the distributed online bandit optimization problem with nonconvex loss functions over a time-varying digraph. This problem can be viewed as a repeated game between a group of online players and an adversary. At each round, each player selects a decision from the constraint set, and then the adversary assigns an arbitrary, possibly nonconvex, loss function to this player. Only the loss value at the current round, rather than the entire loss function or any other information (e.g. gradient), is privately revealed to the player. Players aim to minimize a sequence of global loss functions, which are the sum of local losses. We observe that traditional multi-point bandit algorithms are unsuitable for online optimization, where the data for the loss function are not all a priori, while the one-point bandit algorithms suffer from poor regret guarantees. To address these issues, we propose a novel one-point residual feedback distributed online algorithm. This algorithm estimates the gradient using residuals from two points, effectively reducing the regret bound while maintaining O(1) sampling complexity per iteration. We employ a rigorous metric, dynamic regret, to evaluate the algorithm's performance. By appropriately selecting the step size and smoothing parameters, we demonstrate that the expected dynamic regret of our algorithm is comparable to existing algorithms that use two-point feedback, provided the deviation in the objective function sequence and the path length of the minimization grows sublinearly. Finally, we validate the effectiveness of the proposed algorithm through numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

Attack Impact Evaluation for Stochastic control systems through Alarm Flag State Augmentation

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arXiv 2023年

作者： Sasahara, Hampei Tanaka, Takashi Sandberg, Henrik The Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo152-8552 Japan The Department of Aerospace Engineering and Engineering Mechanics Cockrell School of Engineering The University of Texas AustinTX78712 United States The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

This note addresses the problem of evaluating the impact of an attack on discrete-time nonlinear stochastic control systems. The problem is formulated as an optimal control problem with a joint chance constraint that forces the adversary to avoid detection throughout a given time period. Due to the joint constraint, the optimal control policy depends not only on the current state, but also on the entire history, leading to an explosion of the search space and making the problem generally intractable. However, we discover that the current state and whether an alarm has been triggered, or not, is sufficient for specifying the optimal decision at each time step. This information, which we refer to as the alarm flag, can be added to the state space to create an equivalent optimal control problem that can be solved with existing numerical approaches using a Markov policy. Additionally, we note that the formulation results in a policy that does not avoid detection once an alarm has been triggered. We extend the formulation to handle multi-alarm avoidance policies for more reasonable attack impact evaluations, and show that the idea of augmenting the state space with an alarm flag is valid in this extended formulation as well. © 2023, CC BY-NC-ND.

关键词： Stochastic systems

Proposal of a novel peeling of nano-particle (PNP) process for localized material removal on a hard material surface by controllable magnetic fields 22

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Proposal of a novel peeling of nano-particle (PNP) process f...

22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Permpatdechakul, Thitipat Khajornrungruang, Panart Suzuki, Keisuke Kutomi, Shotaro Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Avanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

This article proposes a novel Peeling of Nano-Particle (PNP) process to locally remove material on a hard material surface using controllable magnetic fields. Fe3O4 particles in the size range of 50-100 nm in aqueous solution (pH value 11 adjusted by KOH) were magnetically controlled to adhere and remove from a 4H-SiC surface by two electromagnetic coils, which were sandwiched between the substrate. The particle controlling phenomenon on the surface was experimentally observed and verified by our developed apparatus applying an evanescent field. According to the results, particles could be controlled to approach and remove from the substrate surface with 12mT of magnetic field at the selective area on the substrate surface to realise the proposed PNP process. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Magnetic fields

Wirelessly Actuated Rotation-free Magnetic Motor

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Wirelessly Actuated Rotation-free Magnetic Motor

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Umur Ulas Harman Ahmed Hafez Cameron Duffield Zihan Zhao Luke Dixon Daniela Rus Shuhei Miyashita Automatic Control and Systems Engineering Department University of Sheffield Sheffield UK Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Insigneo Institute for in Silico Medicine

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper addresses the challenge of actuating millimetre-sized motors, which are wirelessly driven by external magnetic fields. Traditional approaches, relying on rotating magnetic fields, often inadvertently cause the entire robot – especially if it is small and lightweight – to rotate, instead of a specified shaft in the motor. To overcome this issue, our study introduces a novel mechanism that leverages symmetrically configured magnetic motors to cancel out the torques, thus preventing unwanted rotation of the robot. This is achieved by utilizing a magnetic field along a single axis to induce rotational movement. The design features two millimetre-sized rotating magnets that interact to achieve a 90 ◦ rotation, complemented by an external magnetic field that accomplishes the remaining 270 ◦ , thus completing a full rotation. Furthermore, we demonstrate that applying a perpendicularly oriented magnetic field can inversely affect the motor’s rotation direction. A proof-of-concept experiment employing this mechanism successfully actuated a gripper in a water tank while it is free-floating, showcasing its potential for enhancing robotic applications at the sub-centimeter scale, where the small net torque of a miniature motor is essential.

关键词： Water Shafts Torque Gears Net zero Storage management Motors Permanent magnets Magnetic fields Grippers

Conformal Prediction for Distribution-free Optimal control of Linear Stochastic systems

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arXiv 2024年

作者： Vlahakis, Eleftherios E. Lindemann, Lars Sopasakis, Pantelis Dimarogonas, Dimos V. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Thomas Lord Department of Computer Science The Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los AngelesCA90089 United States The School of Electronics Electrical Engineering and Computer Science Queen's University Northern Ireland Belfast United Kingdom

We address an optimal control problem for linear stochastic systems with unknown noise distributions and joint chance constraints using conformal prediction. Our approach involves designing a feedback controller to maintain an error system within a prediction region (PR). We define PRs as sublevel sets of a nonconformity score over error trajectories, enabling the handling of joint chance constraints. We propose two methods to design feedback control and PRs: one through direct optimization over error trajectory samples, and the other indirectly using the S-procedure with a disturbance ellipsoid obtained from data. By tightening constraints with PRs, we solve a relaxed problem to synthesize a feedback policy. Our method ensures reliable probabilistic guarantees based on marginal coverage, independent of data size. © 2024, CC BY.

关键词： Optimal control systems

Robust control of Feeding Speed for Coal Mine Tunnel Drilling Machines

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Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

IEEE International Conference on Industrial Technology (ICIT)

作者： Xiao Liu Luefeng Chen Min Wu Weihua Cao Chengda Lu Witold Pedrycz School of Automation China University of Geosciences Wuhan China School of Automation the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed.

关键词： Drilling Robust control Uncertainty Robust stability Simulation Coal Resonance