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International Electrical engineering Congress (iEECON)

作者： Panjawee Rakprayoon Akechai Ounsiri Ratchanon Chongyoa Dept. AI Engineering and Data Science Faculty of Engineering Bangkok University Pathum Thani Thailand DNA ROBOTICS and Automation System Company Limited Pathum Thani Thailand Dept. Computer and Robotics Engineering Faculty of Engineering Bangkok University Pathum Thani Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

For an AI tic-tac-toe manipulator application, a real-time vision-based approach is proposed. The technique employs the RealSense camera to capture color and dept. images. Combining object detection and image processing techniques to identify X's and O's positions on the game board. However, we recognize that errors can occur during object movement when using only 2D images. To solve this problem, a calibration method between RealSense and the manipulator based on the point-to-plane ICP algorithm is presented. This method provides the 3D object position in the robot coordinate, resulting in increasing the accuracy from 86.25% to 97.25%. Our experiment shows that this technique is highly effective and can accurately identify position objects.

关键词： Three-dimensional displays Robot kinematics Robot vision systems Games Object detection Manipulators Real-time systems

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Change Bit-dept. Procedure for Data Measured Preprocessing before Compression

Change Bit-Depth Procedure for Data Measured Preprocessing b...

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2022 IEEE International Multi-Conference on engineering, Computer and Information Sciences, SIBIRCON 2022

作者： Levenets, Alexey V. Bondarenko, Vladislav V. Bahenov, Ruslan I. Belozerov, Oleg I. Belozerova, Svetlana I. Bogatenkov, Sergey A. Pacific National University Dept. Automation and System Engineering Khabarovsk Russia Sholom-Aleichem Priamursky State University Dept. Information Systems and Mathematics Birobidzhan Russia Far Eastern State Transport University Dept. Computer Technology and Computer Graphics Khabarovsk Russia South Ural State University Dept. Information Technology in Economics Chelyabinsk Russia

ISBN: (纸本)9781665464802

The paper proposes to change the bit-dept. of the original data sequence as a preprocessing of the measuring data, which is carried out before the compression procedure. In this case the digit capacity conversion is performed without accounting for the primary data sample boundaries. The simulation was carried out in the Matlab software environment. The findings of the authors' research are presented. They prove to be a promising approach for some types of the studied data at least and several digit capacity values. The analysis of autocorrelation function values showing the data correlation revealed by the conversion is used as an assessment of perspective of the active conversion. In this article the authors review the values of secondary maximums of autocorrelation function. Their occurrence shows the demonstration of the implied correlative correspondence. Such correlations can potentially allow the converted data to be compressed more effectively than the original data using the known compression methods. © 2022 IEEE.

关键词： Data compression

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A Probabilistic Topology Inference Method for Networked Dynamical system via Single Excitation

A Probabilistic Topology Inference Method for Networked Dyna...

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IEEE Conference on Decision and Control

作者： Qing Jiao Yushan Li Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

A growing number of works have investigated inferring the topology of networked dynamical systems from observations, such as to better understand the system behaviour. Despite the tremendous advances, most of them require the observations to be abundant. This paper focuses on inferring the topology by injecting single excitation on a node and collecting several steps of noisy observations. The problem is challenging because the noises cannot be depressed in several observations and are mixed with the injected excitation, making it hard to directly reveal the topology. To practice, we develop a probabilistic method based on the hypothesis test framework. First, we infer the neighbors that are within h-hop of the excited node and derive the accuracy guarantees. Then, we extend the method to infer the exact h-hop neighbors. A computable lower bound for the accuracy probability is established to provide confidence support in the inference procedures. Furthermore, we give the conditions of excitation input to ensure a desired inference probability, which provides guidance for the input design. Numerical simulations are conducted to verify the effectiveness of the proposed method.

关键词： Lower bound Accuracy Network topology Noise Probabilistic logic Numerical simulation Topology Noise measurement Reliability Dynamical systems

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Hybrid HHO-Wavenet Model Applies in Short-term Load Forecasting for Microgrid system 6

Hybrid HHO-Wavenet Model Applies in Short-term Load Forecast...

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6th International Conference on Green Technology and Sustainable Development, GTSD 2022

作者： Nguyen, Thanh-Hoan Pham, Quoc-Hung Nguyen, Vu-Thuy Truong, Viet-Anh Nguyen, Huu-Vinh Truong, Dinh Nhon Dept. Information Technology Company Ho Chi Minh Viet Nam Union College Schenectady Dept. Electronic Engineering New York United States Ho Chi Minh City University of Technology and Education Dept. Power System Ho Chi Minh Viet Nam Dept. Human Resources Ho Chi Minh Viet Nam Ho Chi Minh City University of Technology and Education Dept. Electrical Automation Ho Chi Minh Viet Nam

ISBN: (数字)9781665466288

ISBN: (纸本)9781665466288

Power load forecasting is an important issue in a microgrid (MG) energy management. Accurate load forecasting is urgently required for effective power management for MG. This paper proposes a new method for short-term load forecasting (STLF). This method uses both long and short data series provided for a Wavenet-based model inspired by a Long Short-Term Memory (LSTM), to forecast hourly load demand. To increase the accuracy of the prediction model, this study used the Harris Hawks Optimization (HHO) algorithm to include in the calculation in the Wavenet network. In order to demonstrate the effectiveness of the model, we work with the load data set of an MG model belonging to the Ho Chi Minh City power grid. The forecasting model is compared with the previous forecasting models. The results show that our proposed model outperforms other deep learning-based models in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE). © 2022 IEEE.

关键词： Forecasting

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An OpenPLC-based Active Real-time Anomaly Detection Framework for Industrial Control systems

An OpenPLC-based Active Real-time Anomaly Detection Framewor...

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2022 Chinese automation Congress, CAC 2022

作者： Zheng, Chengxu Wang, Xiaopeng Luo, Xiaoyu Fang, Chongrong He, Jianping Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education of China And Shanghai Engineering Research Center of Intelligent Control and Management The Dept. of Automation Shanghai China NSFOCUS Technologies Group Co. Ltd Beijing China

ISBN: (纸本)9781665465335

In recent years, the design of anomaly detectors has attracted a tremendous surge of interest due to security issues in industrial control systems (ICS). Restricted by hardware resources, most anomaly detectors can only be deployed at the remote monitoring ends, far away from the control sites, which brings potential threats to anomaly detection. In this paper, we propose an active real-time anomaly detection framework deployed in the controller of OpenPLC, which is a standardized open-source PLC and has high scalability. Specifically, we add adaptive active noises to control signals, and then identify a linear dynamic system model of the plant offline and implement it in the controller. Finally, we design two filters to process the estimated residuals based on the obtained model and use χ2 detector for anomaly detection. Extensive experiments are conducted on an industrial control virtual platform to show the effectiveness of the proposed detection framework. © 2022 IEEE.

关键词： Anomaly detection

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Collaborative Learning in Bilateral Academic Training on Robotics Design and Development

Collaborative Learning in Bilateral Academic Training on Rob...

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STEM Education Conference (iSTEM-Ed), International

作者： Patinya Sang-Aroon Sethakarn Prongnuch Tadchanon Chuman Aphirak Thitinaruemit Kalaphath Kounlaxay Chanida Niyomtum Dept. of Industrial Design and Packaging Faculty of Engineering and Industrial Technology Suan Sunandha Rajabhat University Dusit Bangkok Thailand Dept. of Robotics Engineering Faculty of Engineering and Industrial Technology Suan Sunandha Rajabhat University Dusit Bangkok Thailand Dept. of Electrical Technology Faculty of Engineering and Industrial Technology Suan Sunandha Rajabhat University Dusit Bangkok Thailand Dept. of Computer Engineering Faculty of Engineering Souphanouvong University Luangprabang City Lao PDR Education Automation System Co. Ltd. Bangplee Samutprakran Thailand

ISBN: (数字)9798350365979

ISBN: (纸本)9798350365986

This paper presents how collaborative learning can facilitate academic training in robotics design and development, with the objective of establishing a foundation in robotics structure design and microcontroller programming for controlling robots, particularly for bilateral undergraduate students. The students comprise 20 engineering students and 20 architecture students, who are divided into groups of two, consisting of an engineering students and an architecture students each. Group activities focusing on robot structure design and robot Development are provided for the students. The results demonstrate that collaborative learning can effectively facilitate the training activities.

关键词： Training Educational robots Federated learning Microcontrollers Focusing engineering students Programming profession

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Robot-Assisted Navigation for Visually Impaired through Adaptive Impedance and Path Planning

Robot-Assisted Navigation for Visually Impaired through Adap...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Pietro Balatti Idil Ozdamar Doganay Sirintuna Luca Fortini Mattia Leonori Juan M. Gandarias Arash Ajoudani HRI2 Lab Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy Systems Engineering and Automation Department Robotics and Mechatronics Lab University of Malaga Malaga Spain

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a framework to navigate visually impaired people through unfamiliar environments by means of a mobile manipulator. The Human-Robot system consists of three key components: a mobile base, a robotic arm, and the human subject who gets guided by the robotic arm via physically coupling their hand with the cobot’s end-effector. These components, receiving a goal from the user, traverse a collision-free set of waypoints in a coordinated manner, while avoiding static and dynamic obstacles through an obstacle avoidance unit and a novel human guidance planner. With this aim, we also present a legs tracking algorithm that utilizes 2D LiDAR sensors integrated into the mobile base to monitor the human pose. Additionally, we introduce an adaptive pulling planner responsible for guiding the individual back to the intended path if they veer off course. This is achieved by establishing a target arm end-effector position and dynamically adjusting the impedance parameters in real-time through a impedance tuning unit. To validate the framework we present a set of experiments both in laboratory settings with 12 healthy blindfolded subjects and a proof-of-concept demonstration in a real-world scenario.

关键词： Target tracking Navigation Robot kinematics End effectors Real-time systems Path planning Sensors

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MMC Based D-STATCOM Control by Using a Modified ADRC Strategy

MMC Based D-STATCOM Control by Using a Modified ADRC Strateg...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： João A. Moor Neto Alessando R. Zachi Braulio Chuco Paucar Thiago Americano Do Brasil Samir Ahmad Mussa Department of Electrical Engineering CEFET-RJ Rio de Janeiro Brazil Department of Control System and Automation Engineering CEFET-RJ Rio de Janeiro Brazil Dept. of Electrical and Electronic Engineering UFSC - SC Florianopolis Brazil

This paper presents investigations of a transformerless half bridge sub-module (HBSM) modular multilevel converter based distribution static synchronous compensator (MMC D-STATCOM) performance in reactive power compensation considering the application of the modified ADRC controllers in the inner current loop and in the outer DC voltage loop using Synchronous Reference Frame Control. Simulation results with the imposition of severe variations in reactive loads were obtained on a 5 km medium voltage feeder and will demonstrate that the modified ADRC controller enables superior performance for flexible operation with fast and efficient response of the MMC D-STATCOM in reactive power compensation.

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Preserving Topology of Network systems: Metric, Analysis, and Optimal Design

arXiv

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arXiv 2023年

作者： Li, Yushan Wang, Zitong He, Jianping Chen, Cailian Guan, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless, recent works have revealed that the topology cannot be preserved under i.i.d. noises in the asymptotic sense. How to effectively characterize the non-asymptotic preservation performance still remains an open issue. Inspired by the deviation quantification of concentration inequalities, this paper proposes a novel metric named trace-based variance-expectation ratio. This metric effectively captures the decaying rate of the topology inference error, where a slower rate indicates better non-asymptotic preservation performance. We prove that the inference error will always decay to zero asymptotically, as long as the added noises are non-increasing and independent (milder than the i.i.d. condition). Then, the optimal noise design that produces the slowest decaying rate for the error is obtained. More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously. Extensions to a general class of noises with multi-lag time dependence are provided. Comprehensive simulations verify the theoretical findings. Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

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Optimal Linear Attack in Cyber-Physical systems with Periodic Detection

Optimal Linear Attack in Cyber-Physical Systems with Periodi...

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IEEE Conference on Decision and Control

作者： Jia Qi Chongrong Fang Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Security issues are of significant importance for cyber-physical systems (CPS), where the attack design is a major concern. Most related studies on attack design implicitly consider that the control period and detection period are the same. However, the two periods could be different in practical systems with remote detection such as supervisory control and data acquisition (SCADA) systems, which could lead to new vulnerabilities for attackers. In this paper, we consider the design of innovation-based linear attack strategies for CPS when the control period and detection period are inconsistent. Specifically, we propose an attack framework that consists of attack strategies for detection and non-detection instants under the period discrepancy. On this basis, we design the optimal stealthy innovation-based linear attack strategies for state estimation and LQG control to maximize the estimation error or control cost, respectively. Simulations are given to demonstrate the effectiveness of the proposed attack strategies.

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