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Application of a systematic approach to the analysis of requirements and testing of NPP automated process control systems in the field of information security using specialized software

Application of a systematic approach to the analysis of requ...

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2021 International Conference on Electrotechnical Complexes and systems, ICOECS 2021

作者： Kemkin, Vladislav Doroshenko, Boris Sakharov, Konstantin Salov, Igor Salova, Julia Chernyaev, Alexey National Research University 'Moscow Power Engineering Institute' Dept. of Automated Control Systems for Thermal Processes Moscow Russia Joint-stock Company 'Rasu' Dept. of Design of I&C Computer Security Systems Moscow Russia National Research University 'Moscow Power Engineering Institute' Joint-stock Company 'Rasu' Dept. of Automated Control Systems for Thermal Processes Moscow Russia

ISBN: (纸本)9781665407274

This article reports examines the prerequisites for development and the expected results of the application of a new systematic approach to testing Industrial control System of Nuclear Power Plants (NPP ICS) in the field of information security using specialized software. The regulatory and technical documentation containing the requirements for testing the NPP ICS in the field of information security is considered, the requirements are analyzed and criteria for systematization of these requirements are formed. The result of the research is the creation of a systematic list of requirements for testing of NPP ICS subsystems in terms of information security, as a basis for the software of formation of programs, methods of checking and testing of NPP ICS subsystems in terms of information security. © 2021 IEEE.

关键词： Application programs

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Feedforward control in the Presence of Input Nonlinearities: A Learning-based Approach

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IFAC-PapersOnLine 2022年第37期55卷 235-240页

作者： Jilles van Hulst Maurice Poot Dragan Kostić Kai Wa Yan Jim Portegies Tom Oomen Control Systems Technology Section Dept. of Mechanical Engineering Eindhoven University of Technology The Netherlands Center of Competency ASM Pacific Technology The Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology The Netherlands Delft Center for Systems and Control Delft University of Technology The Netherlands

Advanced feedforward control methods enable mechatronic systems to perform varying motion tasks with extreme accuracy and throughput. The aim of this paper is to develop a data-driven feedforward controller that addresses input nonlinearities, which are common in typical applications such as semiconductor back-end equipment. The developed method consists of parametric inverse-model feedforward that is optimized for tracking error reduction by exploiting ideas from iterative learning control. Results on a simulated set-up indicate improved performance over existing identification methods for systems with nonlinearities at the input.

关键词： Nonlinear system identification Identification for control Iterative learning control Data-based control Motion control Applications in semiconductor manufacturing

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Analysis and Detection of Melanoma through Collective Intelligence with AI

Analysis and Detection of Melanoma through Collective Intell...

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Annual IEEE Symposium on computer-Based Medical systems

作者： Enrique Fernández-Morales Carlos L. Sanchez-Bocanegra Rafael Pastor-Vargas José-Juan Pereyra-Rodriguez Juan M. Haut José Alberto Benítez-Andrades Communications and Control Systems Dpt. Computer Science Faculty UNED Madrid Spain Communications and Control Systems Dpt. Computer Science Faculty UNED Malaga Spain Virgen Del Rocio Hospital Universitario Seville Spain School of Tecnology University of Extremadura Cáceres Spain Dept. of Electric Systems and Automatics Engineering Universidad de León León Spain

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Cancer is a widespread global health problem, claiming millions of lives each year, and skin cancer represents a significant threat as it is one of the most common types. Early tumor detection via medical imaging is critical for effective treatment. Leveraging artificial intelligence, particularly novel models like Transformers, presents promising avenues for improved diagnosis. This paper explores the efficacy of a Collective Intelligence approach using AI in classifying cancerous and non-cancerous tumors, aiming to reduce classification errors and support clinical decision-making. We created five different configurations using various datasets to compare the results. The results show solid performance for the CI in the evaluated tasks, reaching up to 75.89% accuracy. The lack of images in certain classes significantly contributes to overfitting. It is suggested to explore data expansion strategies and improve consistency in image capture for future work.

关键词： Accuracy Melanoma Collective intelligence Image capture Transformers Solids Artificial intelligence

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LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle

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IFAC-PapersOnLine 2022年第35期55卷 37-42页

作者： Matthis H. de Lange Chris Verhoek Valentin Preda Roland Tóth Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven 5600 MB The Netherlands ESTEC European Space Agency Noordwijk 2200 AG The Netherlands Systems and Control Lab Institute for Computer Science and Control Budapest 1111 Hungary

Obtaining models that can be used for flight control is of outmost importance to ensure reliable guidance and navigation of spacecrafts, like a Generic Parafoil Return Vehicle (GPRV). In this paper, we convert an existing, high-fidelity nonlinear model of the atmospheric flight dynamics of a GPRV to a Linear Parameter-Varying (LPV) form that enables high-performance navigation control design. Application of existing systematic conversion methods for such complicated nonlinear models often result in complex LPV representations, which are not suitable for controller synthesis. We apply and compare state-of-the-art conversion techniques on the GPRV model, including learning based approaches, to optimize the complexity and conservatism of the resulting LPV embedding. The results show that we can obtain an LPV embedding that approximates the complex nonlinear dynamics sufficiently well, where the balance between complexity, conservatism and model performance is efficiently chosen.

关键词： linear parameter-varying systems scheduling reduction spacecraft modeling aerodynamics principle component analysis deep neural networks

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Client-server Mobile System for Diagnosis of Asynchronous Motors 4

Client-server Mobile System for Diagnosis of Asynchronous Mo...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Chorna, Olha Kurliak, Petro Busher, Victor Chornyi, Oleksii Tytiuk, Valerii Zachepa, Iurii Institute of Education and Science in Electrical Engineering and Information Technologies Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Department of Electrical Power Engineering Electrical Engineering And Electromechanics Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Dept. of Electrical Engineering and Electronics National University "Odessa Maritime Academy" Odessa Ukraine Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

ISBN: (纸本)9798350395532

This paper presents client-server mobile system for diagnosis of asynchronous motors. The system is created as a mobile application for smartphones and tablets. The system provides processing of the measured values of the currents and voltages of the stator phases of the asynchronous motor. According to the processing results, the results of diagnostics and forecasting of the current state of asynchronous motors are calculated. The software runs on the Android OS. The main purpose is to predict the current state of AD, which has a parametric electromagnetic asymmetry of the stator phases. © 2023 IEEE.

关键词： Induction motors

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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine

Process-Model-Free Design of MPC via a Reference-Model-Based...

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Electrical engineering, control and Robotics (EECR), International Conference on

作者： Gengjin Shi Chengbo Dai Miaomiao Ma Donghai Li Yanjun Ding Dept. of Energy & Power Engineering State Key Lab of Power Systems Tsinghua University Beijing China School of Control & Computer Engineering North China Electric Power University Beijing China

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller – desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine.

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Modular Hardware, Open Source Software and Training Material for PLC Training

Modular Hardware, Open Source Software and Training Material...

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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Harsha Priyanka Guntaka Rajesh Kushalkar Nirmala Venkat Akshay Chipkar Vishnu Easwaran Kannan Moudgalya Dept. of Systems & Control Engineering IIT Bombay Mumbai India Dept. of Computer Science & Enginering IIT Bombay Mumbai India Dept. of Chemical Engineering IIT Bombay Mumbai India

ISBN: (纸本)9781665490498

A low cost, open source, rugged, modular OpenPLC, based on ATmega16 microcontroller, has been developed for instructional purposes. Modularity permits flexible use of the OpenPLC. The open source software LDmicro, created for ladder logic operations, has been enhanced, and ported to Linux. A total of 27 Spoken Tutorials of about 10 minute duration each, suitable for self learning, are created for OpenPLC training. A pilot workshop is conducted for 16 teachers of polytechnic colleges using the Spoken Tutorials and the simulation capability of LDmicro. The feedback from the workshop is positive, and the method is suitable for a large scale training.

关键词： Training Mechatronics Costs Automation Microcontrollers Conferences Linux

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Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

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arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

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Contagion Propagation with Rule-Based Reasoning and Decentralized control in an Agent-Based Susceptible-Infected-Recovered-Susceptible Infodemic Model

Contagion Propagation with Rule-Based Reasoning and Decentra...

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Big Data, Knowledge and control systems engineering (BdKCSE)

作者： Cristian Berceanu Nadia Arshad Monica Patrascu Dept. of Automatic Control and Systems Engineering Complex Systems Laboratory University Politehnica of Bucharest Bucharest Romania Dept. of Global Public Health and Primary Care Section for Epidemiology and Medical Statistics University of Bergen Bergen Norway Complex Systems Laboratory University Politehnica of Bucharest Dept. of Global Public Health and Primary Care Centre for Elderly and Nursing Home Medicine University of Bergen Bergen Norway

In recent years, and especially during the on-going pandemic, the interest in investigating the dynamics of infodemics has increased to unprecedented levels. In this study we propose an agent-based model for the spread of misinformation, disinformation, and other similar information. The model is based on the susceptible-infected-recovered-susceptible epidemic interpretation. We introduce a rule-based reasoning module to model individual bias in the perception of information based on the psychology concept of illusion of knowledge. We integrate this module into a deliberative-reactive agent controller structure and a decentralized control scheme for the multi-agent system. Results show significant differences between the outputs of the proposed model and the classical version, impressing on the effects of considering local agent individuality when modeling human psycho-social interactions.

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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Electronic engineering (ICEEM), International Conference on

作者： Mahmoud Elshabrawy Marwa M. Eid Abdelaziz A. Abdelhamid El-Sayed M. El-Kenawy Abdelhameed Ibrahim Dept. of Communications & Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Dep. of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Engineering and Control Systems Dept. Faculty of Engineering University Mansoura Egypt

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models.

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