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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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Test automation of DCS controller’s Communication Interface

Test Automation of DCS Controller’s Communication Interface

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International Conference on Computing and Networking Technology (ICCNT)

作者： Adluri Srikar Girish Nadig Yogesh Alawani Sunil Kumar T. K. Dept. of Electrical Engineering National Institute of Technology Calicut Kerala India Process Automation – Process Control Platform (PA-PCP) ABB Global Industries and Services Private Limited Bengaluru India

Modbus over TCP/IP has become one of the most utilised industrial protocols for networking critical infrastructure. It is crucial to test how the ABB 800xA DCS controller's Modbus TCP/IP protocol functions at both the component-level and the functional-level. Whereas manual testing takes a lot of time to build up a test environment. For example connecting the hardware like end devices, launching the controller (which executes the settings and programs created in the DCS software), configuring the DCS software tool (which enables editing, compilation, testing, and downloading of the desired controller programs to the controller), developing or loading controller programs which has different configurations, modifying the application variables, and also manually providing the input values into the desired registers or coils using Modbus slaves. Therefore, there is a great need to automate the entire process so that it becomes less repetitious, more effective, and requires less human effort. After comparing some available tools, We decided on SpecFlow as the point of entry into the automation framework. By connecting business-readable behavioral needs to the actual implementation, this tool "seeks to narrow the interaction gap between domain-specific experts and developers," according to its description. Our approach takes an array of steps defined in the Gherkin language using the SpecFlow framework as its input and embeds them inside step definition files developed using the C# language and *** framework. Additionally, PyModbusTCP served as the Modbus slave in the above project, providing complete test automation. PyModbusTCP is a slave-generation library built on the Python programming language. The Modbus Client object is used to provide access to the Modbus/TCP server.

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Cyber-resilience for marine navigation by information fusion and change detection

arXiv

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arXiv 2022年

作者： Dagdilelis, Dimitrios Blanke, Mogens Andersen, Rasmus H. Galeazzi, Roberto Automation and Control Group Dept. of Electrical Engineering Technical University of Denmark Elektrovej B 326 Kgs. Lyngby2800 Denmark

Cyber-resilience is an increasing concern in developing autonomous navigation solutions for marine vessels. This paper scrutinizes cyber-resilience properties of marine navigation through a prism with three edges: multiple sensor information fusion, diagnosis of not-normal behaviours, and change detection. It proposes a two-stage estimator for diagnosis and mitigation of sensor signals used for coastal navigation. Developing a Likelihood Field approach, a first stage extracts shoreline features from radar and matches them to the electronic navigation chart. A second stage associates buoy and beacon features from the radar with chart information. Using real data logged at sea tests combined with simulated spoofing, the paper verifies the ability to timely diagnose and isolate an attempt to compromise position measurements. A new approach is suggested for high level processing of received data to evaluate their consistency, that is agnostic to the underlying technology of the individual sensory input. A combined parametric Gaussian modelling and Kernel Density Estimation is suggested and compared with a generalized likelihood ratio change detector that uses sliding windows. The paper shows how deviations from nominal behaviour and isolation of the components is possible when under attack or when defects in sensors occur. © 2022, CC BY.

关键词： Data handling

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Evaluation of Deep Training and Adapting Algorithms in Medical with De-Noising EEG 3

Evaluation of Deep Training and Adapting Algorithms in Medic...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Abdulwahid, Ali Hadi Karetla, Girija Rani Ganesh, K.V.B. Kumar, A Suresh Radha, K. Shivakumar, K. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Western Sydney University School of Computer Data and Mathematical Sciences Australia Koneru Lakshmaiah Education Foundation KL Business School Guntur Andhra Pradesh India Graphic Era Deemed to Be University Department of CSE India St. Martin's Engineering College Dept. of IT Secunderabad Telangana India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India

ISBN: (纸本)9798350399264

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least-square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal-to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods. © 2023 IEEE.

关键词： Electroencephalography

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Computing Platform for Monitoring Fire Hazards in Forest Areas using the IoT

Computing Platform for Monitoring Fire Hazards in Forest Are...

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International Seminar on Electron Devices Design and Production (SED)

作者： A.A. Sorokin I.O. Odnogulov N.S. Maltseva E.A. Dzhalmukhambetova M.F. Rudenko V.N. Esaulenko dept. of Telecommunication Astrakhan State Technical University Astrakhan Russia dept. of Mathematical and Natural Sciences Caspian Institute of Sea and River Transport named after General-Admiral F. M. Apraksin — branch of Volga State University of Water Transport Astrakhan Russia dept. of Life safety and environmental engineering Astrakhan State Technical University Astrakhan Russia dept. of Automation and control Astrakhan State Technical University Astrakhan Russia

ISBN: (数字)9798331505028

ISBN: (纸本)9798331505035

The purpose of this work is to implement a computing platform based on programmable controllers integrated into the Internet of Things (IoT), which are designed for forest fire-fighting monitoring. To calculate the fire hazard assessment, a hierarchical fuzzy inference system (HFIS) has been implemented, which aggregates a set of input parameters characterizing the state of a forest area into a single assessment. When forming this assessment, parameters are taken into account that characterize the state of the climate, the presence of dry trees, the characteristics of the state of combustible materials located on the surface of the earth, as well as the state of peat. The implementation of the computing platform is carried out using a set of Arduino controllers. To test the functionality of the proposed computing complex, its model was implemented in the TinkerCAD simulation environment. Also, using the Python programming language, a similar HFIS was implemented in the form of an independent model. As a result of comparing these two computing complexes, it has been shown that they generate similar results. This fact confirms the possibility of using several Arduino controllers to implement a computing platform based on a HFIS. The proposed provisions are aimed at expanding the IoT networks to build monitoring systems for forests and other natural areas.

关键词： Fuzzy logic Computational modeling Forestry Hazards Software Sensor systems Telecommunications Sensors Internet of Things Monitoring

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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Behavioural Cloning for Serious Games in Support of Pediatric Neurorehabilitation

Behavioural Cloning for Serious Games in Support of Pediatri...

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Mediterranean Conference on control and automation (MED)

作者： Federico Baldisseri Edoardo Montecchiani Arturo Maiani Danilo Menegatti Alessandro Giuseppi Antonio Pietrabissa Vincenzo Fogliati Francesco Delli Priscoli Dept. of Computer Control and Management Engineering (DIAG) Sapienza University of Rome Italy 4You – Association for Social Advancement Rome Italy Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy

Behavioural Cloning is a Machine Learning method concerning how a machine attempts to autonomously mimic the actions of a human, or in general a complex controller, performing a given task. This work innovatively exploits Behavioural Cloning in support of Pediatric Neurorehabilitation. In particular, an Artificial Neural Network Classifier has been implemented to autonomously adapt the difficulty, through a set of tunable parameters, of a Serious Game that was specifically developed to stimulate some relevant cognitive capabilities of the patient. Data augmentation via Behavioural Cloning allows such autonomous difficulty adaptation system to improve its classification performances and, thus, to enforce a control logic that, in turn, improves the effectiveness of the cognitive training. The system is validated through an experimental assessment on a Serious Game that trains motor coordination: experimental results of children gameplay are analyzed and discussed.

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I Can Read Your Mind: control Mechanism Secrecy of Networked Dynamical Systems under Inference Attacks

arXiv

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arXiv 2022年

作者： He, Jianping Li, Yushan Cai, Lin Guan, Xinping The 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 The Dept. of Electrical and Computer Engineering University of Victoria BC Canada

Recent years have witnessed the fast advance of security research for networked dynamical system (NDS). Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this article focuses on a new security aspect, i.e., how to protect control mechanism secrets from inference attacks, including state information, interaction structure and control laws. We call this security property as control mechanism secrecy, which provides protection of the vulnerabilities in the control process and fills the defense gap that traditional cyber security cannot handle. Since the knowledge of control mechanism defines the capabilities to implement attacks, ensuring control mechanism secrecy needs to go beyond the conventional data privacy to cover both transmissible data and intrinsic models in NDSs. The prime goal of this article is to summarize recent results of both inference attacks on control mechanism secrets and countermeasures. We first introduce the basic inference attack methods on the state and structure of NDSs, respectively, along with their inference performance bounds. Then, the corresponding countermeasures and performance metrics are given to illustrate how to preserve the control mechanism secrecy. Necessary conditions are derived to guide the secrecy design. Finally, thorough discussions on the control laws and open issues are presented, beckoning future investigation on reliable countermeasure design and tradeoffs between the secrecy and control performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Cybersecurity

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Modeling the Productivity of a Sugar Factory using Machine Learning Methods

Modeling the Productivity of a Sugar Factory using Machine L...

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International Computer Sciences and Information Technologies (CSIT)

作者： Nataliia Lutska Lidiia Vlasenko Nataliia Zaiets Vitaliy Lysenko dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350334326

Relevant today is the digitalization of industrial enterprises, which is an evolutionary continuation of the introduction of MES/MOM. At the same time, an important role is played by the construction of mathematical models for various purposes, which are the main component of the Digital Twin development. Digital Twin provides a new philosophy for conducting enterprise production processes based on these models, which is aimed at improving the efficiency of both individual sectors and the enterprise as a whole. To increase the profit of the enterprise, it is necessary to ensure the planned productivity of technological processes, the final indicator of which is the yield of sugar. Taking into account that a significant number of material flows operate at the enterprise, only production flows with which the operator-technologist works are singled out in the work. The selected flows, based on expert assessments, were assigned weighted values of the impact on the overall performance of the sugar production. This made it possible to build a mathematical model that predicts the yield of sugar from input flows. The structure and parameters of this model are determined by machine learning methods. This is a feed-forward neural network MLP 7-23-23-1, which provides forecast accuracy with an error of less than 1%. The model can be used to model, correct, and predict the process conditions of an enterprise, which will increase the overall productivity of the sugar factory.

关键词： Productivity Biological system modeling Machine learning Predictive models Mathematical models Sugar industry Production facilities

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Dual Unscented Kalman Filter Architecture for Sensor Fusion in Water Networks Leak Localization

arXiv

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arXiv 2024年

作者： Romero-Ben, Luis Irofti, Paul Stoican, Florin Puig, Vicenç Institut de Robòtica i Informàtica Industrial CSIC-UPC Spain LOS-CS-FMI University of Bucharest Romania The Universitat Politècnica de Catalunya Spain Dept. of Automation Control and Systems Engineering Politehnica University of Bucharest Romania

Leakage in water systems results in significant daily water losses, degrading service quality, increasing costs, and aggravating environmental problems. Most leak localization methods rely solely on pressure data, missing valuable information from other sensor types. This article proposes a hydraulic state estimation methodology based on a dual Unscented Kalman Filter (UKF) approach, which enhances the estimation of both nodal hydraulic heads, critical in localization tasks, and pipe flows, useful for operational purposes. The approach enables the fusion of different sensor types, such as pressure, flow and demand meters. The strategy is evaluated in well-known open source case studies, namely Modena and L-TOWN, showing improvements over other state-of-the-art estimation approaches in terms of interpolation accuracy, as well as more precise leak localization performance in L-TOWN. Copyright © 2024, The Authors. All rights reserved.

关键词： Kalman filters

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