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10th IEEE Joint International Information Technology and Artificial Intelligence conference, ITAIC 2022

作者： Shen, Yafeng Zhang, Jinkun Chen, Quangen Deng, Fei Zhang, Yi Institute of Computer Applications Chinese Academy of Engineering Physics Sichuan China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

The missile fuze control system, is the most central functional component of the strategic missile control system. In the trend of increasingly strong combat target protection, how to improve the accuracy of detonation, accurate and timely detonation and give full play to the power of strategic weapons under the circumstances of high complexity and uncontrollable external environmental factors, is an important research hotspot in the field of fuze control technology. High reliability and safety have always been extremely important indicators for fuze control systems. In this paper, we use Timed CSP# (Communicating Sequential processes, CSP), a sequential process language with time, to model, analyze and verify the fuze control system, and analyze it with the actual engineering test results to find the design that meets the requirements by modifying the model and being able to feed back to the design of the requirements to realize the combination of testing and verification to improve software reliability and safety. We focus on the modules for real-time distributed interaction in the core functions of the fuze control system, analyze and verify the communication and interaction logic, data analysis and decision making between each module. we simulate and model check the constructed model by process analysis Toolkit (PAT), describe the key properties of the system by the timing logic formula LTL, and verify the important specifications and properties that need to be satisfied by the analyzed system. We finally found 2 system design defects through formal method modeling verification, which were highly accepted by system designers and testers. The use of formal methods for modeling and verification analysis of missile fuze control systems can effectively improve the safety and reliability of fuze control systems. © 2022 IEEE.

关键词： Formal verification

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Automatic Classification of Working Activities for Risk Assessment in Large-Scale Retail Distribution by UsingWearable Sensors: A Preliminary analysis 1

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13th International conference on Digital Human modeling and Applications in Health, Safety, Ergonomics and Risk Management (DHM) Held as Part of the 24th International conference on Human-Computer Interaction (HCii)

作者： Andreoni, Giuseppe Cassiolas, Giorgio Standoli, Carlo Emilio Lenzi, Stefano Elio Perego, Paolo Lopomo, Nicola Francesco Politecn Milan Dipartimento Design Milan Italy Univ Brescia Dipartimento Ingn Informaz Brescia Italy Univ Verona Dipartimento Neurosci Biomed & Movimento Verona Italy

ISBN: (数字)9783031060182

ISBN: (纸本)9783031060182;9783031060175

Providing reliable information on human activities and behaviors is an extremely important goal in various application areas such as healthcare, entertainment, and security. Within the working environment, a correct identification of the actual performed tasks can provide an effective support in the assessment of the risk associated to the execution of the task itself, and thus preventing the development of work-related musculoskeletal diseases. In this perspective, wearable-based Human Activity Recognition systems have been representing a prominent application. This study aimed to compare three different classification approaches appointed from supervised learning techniques, namely k-Nearest Neighbors, Support Vector Machine and Decision Tree. Motion data, related to several working activities realized in the large-scale retail distribution, were collected by using a full-body system based on 17 Inertial Measurement Units(MVN Analyze, XSens). Reliable features in both time- and frequency-domain were first extracted from raw 3D accelerations and angular rates data, and further processed by Principal Component analysis, with 95% threshold. The classification models were validated via 10-fold cross-validation on a defined training dataset. k-Nearest Neighbors classifier, which provide the best results on the training session, was eventually tested for generalization on additional data acquired on few specific tasks. As a result, considering 5 main macro activities, k-Nearest Neighbors provided a classification accuracy of 80.1% and a computational time of 1865.5 s. To test the whole assessment process, the activities labelled by the classification model as handling of low loads at high frequency were automatically evaluated for risk exposure via OCRA Checklist method.

关键词： Human activity classification Wearable technology Machine learning Risk assessment Work-related diseases Large-scale retail distribution

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Plant modeling and Estimation Framework for a Plume-Generating controlled Underwater Vehicle

Plant Modeling and Estimation Framework for a Plume-Generati...

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Mediterranean conference on control and Automation (MED)

作者： Nicholas Orlovsky Michael A. Demetriou Nikolaos A. Gatsonis Aerospace Engineering Department Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

The use of autonomous underwater vehicles (AUVs) for the real-time estimation of a plume generated by an underwater stationary or moving source finds important applications. A mathematical estimation framework is presented that includes the process-state (plume) model described by the 3D advection-diffusion partial differential equation and the exosystem (moving source) with a 6 DOF dynamical model and a guidance scheme. The process-state model is discretized using a non-overlapping domain decomposition finite volume method with Runge-Kutta integration. The source is following a physics-based prescribed trajectory with a PID controller. Numerical results show grid sensitivity analysis for the process-state under realistic underwater tidal currents and diffusivities. Plant data are shown for a typical case of a moving source in a large simulation domain and realistic ambient conditions.

关键词： Solid modeling Accuracy Three-dimensional displays Estimation process control Mathematical models 6-DOF

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Route Planning and control of Intelligent Robot Based on Artificial Intelligence and Virtual Simulation

Route Planning and Control of Intelligent Robot Based on Art...

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2023 International conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Huang, Zhiqiang Wei, Yuhua Guangzhou Huali Science and Technology Vocation College Guangzhou China

ISBN: (纸本)9798350313413

With the continuous research and development of robotics, intelligent robots have gradually moved from theoretical research to practical applications, and among them, AGV (Automatic Guided Vehicle)have attracted the most attention. Therefore, it is very necessary to sztudy the trace layout and control methods of AGV. On this basis, this paper focuses on the trace layout and control methods of intelligent robots during the movement process, and gives corresponding solutions to the collision and obstacle avoidance problems of intelligent robots. First of all, the more general ROS system is used as the development operating system of the robot, and the three-dimensional modeling and kinematic analysis of the robot are carried out to complete the robot software design. Then, by analyzing the problems existing in the traditional A∗ algorithm, the route planning algorithm is improved. Finally, the improved algorithm is simulated and compared with data. The experimental results show that the improved A∗ algorithm reduces the average number of search grids by 56.77%, the average search time by 75.64%, and the average path length by 8.16%, which is suitable for the global path of the robot. © 2023 IEEE.

关键词： intelligent algorithm intelligent robot route planning virtual simulation environment

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UniNetProbe: A Comprehensive 5G Research Testbed Framework

UniNetProbe: A Comprehensive 5G Research Testbed Framework

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IEEE International Workshop on Computer-Aided modeling, analysis, and Design of Communication Links and Networks, CAMAD

作者： P. Papaioannou G. Tziavas D. Giannopoulos C. Tranoris S. Denazis Dept. of Electrical and Computer Engineering University of Patras Patras Greece

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

A well-defined and well-designed experimentation process is crucial for meaningful research outcomes. This paper introduces a framework aimed at streamlining the experimentation process in networking testbeds, consisting of five key components: i) the experiment driver, containing available experiment tools, ii) the control tools to enhance capabilities and create complex scenarios, iii) the monitoring implementation, providing researchers with meaningful insights into gathered metrics, iv)the database component, which will be the main repository for storing experimental results and v) the analytics component, which could provide insights on patterns and hidden knowledge found in the extracted data, with the help of algorithms and artificial intelligence. The framework can be applied to various networking testbeds and is followed by descriptions of two Proof of Concepts (PoCs) demonstrating its implementation.

关键词： Measurement Knowledge engineering Analytical models 5G mobile communication databases conferences Computational modeling process control data mining Monitoring

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Automatic Temperature control of Blast Furnace Based on data analysis Model 2

Automatic Temperature Control of Blast Furnace Based on Data...

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2nd International conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Wang, Xijuan Feng, Jingxiao School of Physics and Electronic Information Luoyang Normal University Luoyang471000 China

ISBN: (纸本)9781510657717

The heating process of the blast furnace is a complex and huge controlled object, which has the characteristics of nonlinear, multivariable, distributed parameters, fast and slow processes intertwined. It is impossible to achieve satisfactory control results only by traditional control. With the development of artificial intelligence in recent years, neural networks, expert technology, fuzzy and predictive control provide new ideas for the heating control of the blast furnace. In this paper, based on the deep learning framework of artificial intelligence, the LSTM algorithm is proposed. Based on the massive production data, through the model simulation comparison, the results show that the LSTM network modeling has stronger generalization ability, smaller error, and higher accuracy. The LSTM neural network algorithm can effectively deal with the characteristics of time series data, provide guidance for the production practice, and lay a good foundation for the predictive control of blast furnaces. © 2022 SPIE. All rights reserved.

关键词： Blast furnaces

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modeling and analysis of Residential DC Microgrid Energy Management Using System of Systems Architecture 16

Modeling and Analysis of Residential DC Microgrid Energy Man...

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16th IEEE AFRICON, AFRICON 2023

作者： Masango, Fannie Isaac Jordaan, Jaco Nnachi, Agha Francis Tshwane University of Technology Electrical Engineering South Africa

ISBN: (纸本)9798350336214

Electricity technology advancement in the world increases energy demand. The pollution problems caused by non-renewable fuels have accelerated the use of distributed energy resources (DERs) in all industries. Microgrids have been used in many industries to improve resiliency. Energy Management Systems (EMS) can help enhance microgrids' robustness, ensuring that the grid remains stable and operational long when energy is minimal. EMS allows for centralised monitoring and control of energy use across building systems. It is developed to record, store, and process power consumption data of every major appliance in the house and industries. An Energy Management System consists of different components seen as operational units. Operational units are responsible for measurement, communication, decision-making, and power supply switching control to manipulate the power output to meet the energy demands. If hierarchical control is used on a DC microgrid, efficiency can be improved by introducing a load-shedding concept, minimising downtime. This research aims to model and develop an energy management system in PV/Composite Storage DC microgrid system. An agent-based approach is used in the implementation of the EMS. © 2023 IEEE.

关键词： Energy management systems

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Combining neural networks and control: potentialities, patterns and perspectives

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IFAC-PapersOnLine 2023年第2期56卷 9036-9049页

作者： Sophie Cerf Éric Rutten Univ. Lille Inria CNRS Centrale Lille UMR 9189 CRIStAL F-59000 Lille France Univ. Grenoble Alpes Inria CNRS LIG Grenoble F-38000 France

Machine learning tools are widely used for knowledge extraction, modeling, and decision tasks; a range of problems that control Theory also tackles. Their relations have been largely explored by looking at stochastic control and Markov Decision processes, due to the proximity of their formulations. However, novel links between machine learning and deterministic control are emerging; combining both approaches, e.g. by performing identification with learning, or controlling the training process. The recent flourishing literature is vast: there is a need to identify challenges, trends and opportunities on this interface. This survey contributes i) to the compared analysis of both fields. ii) Based on literature review, a categorization of combinations of learning and control is drawn. In the control framework, learning has been used for modeling, controllers tuning or adaptation, generating a controller or as a controller itself, for translating complex objectives, or checking controlled systems. Conversely, in the learning framework, control is used for tuning hyperparameters, selecting or generating training data, as the training or decision-making algorithm itself or to guarantee learning properties. iii) Finally, discussions on the literature open novel promising combinations to be explored, such as control of neural networks’ training process.

关键词： Machine Learning Neural Networks Learning for control Reinforcement learning and deep learning in control Machine learning in modelling prediction control and automation data-driven control

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The Development an IoT-Based Virtual Model of Power Grid System with Renewable Energy Sources for a Laboratory Practicum of control Systems 21st

The Development an IoT-Based Virtual Model of Power Grid Sys...

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21st International conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Stupak, Maryna Telychko, Hanna Stupak, Hlib Potsepaiev, Valerii Donetsk Natl Tech Univ 2 Shybankova Sq UA-85300 Donetsk Ukraine

ISBN: (纸本)9783031618901;9783031618918

Today, Ukraine faces challenges that significantly impact the educational process in higher education institutions. Initially, the COVID-19 pandemic and later the war have hindered students' ability to develop hard skills effectively. Approximately 50% of students in technical universities in Ukraine lack access to laboratories for practical training. To compensate for educational losses and enhance the quality of practical training, it is essential to focus efforts on virtualizing laboratories and ensuring remote continuous access to them. Modern technologies and cloud services enable the creation of digital twins of technological processes that can replace physical equipment, conduct simulation modeling of various systems, create interactive systems, and allow students to research and test solutions they have developed in a safe environment. This realization method ensures uninterrupted access to educational content for learners, regardless of their actual location and at a convenient time in secure conditions. The result of this work is a prototype IoT system created using databases, Node-RED, and protocols such as MQTT, HTTP/HTTPS, among others. The developed IoT system familiarizes education seekers with examples of building geographically distributed computer-integrated networks for automation and monitoring of control object statuses using Industry 4.0 and IoT. The virtual model of the IoT system represents a power grid consisting of consumers, power plants, and renewable energy sources. All model components interact in a unified information space, allowing students to gain practical experience in virtual environments with networking technologies, programming, data analysis, and control algorithm development. This work was supported by the European Commission [grant number ENI/2019/413-664 "EDUTIP"] and Edunet World Association (EWA).

关键词： Industry 4.0 Virtual Laboratory Green Transition Cloud Technologies IoT/iioT

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Software Architecture for process Simulation in Biogas Plants

Software Architecture for Process Simulation in Biogas Plant...

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International conference on Advanced Computer Information Technologies (ACIT)

作者： Andriy Melnyk Yurii Maslyiak Pavlo Popovych Taras Sitkar Evhenii Momotiuk Bohdan Kostyk Department of Computer Science West Ukrainian National University Ternopil Ukraine Department of Transport and Logistics West Ukrainian National University Ternopil Ukraine Department of Computer Technologies Ternopil Volodymyr Hnatiuk National Pedagogical University Ternopil Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

The work substantiates the use of modern information technologies and mathematical modeling based on the analysis of interval data as effective process management tools in biogas plants. The use of interval modeling allows you to build models with guaranteed prognostic properties. The article also presents the features of building the software architecture for mathematical modeling of processes in biogas plants. The main aspects of the implementation of software for modeling processes in biogas plants are described, the feature of which is the software interpretation of interval discrete models and an open service-oriented architecture, which ensures their integration into existing control systems of biogas plants and allows to control biochemical processes in real time and thereby increase efficiency of functioning of biogas plants. A number of diagrams illustrating the features of the software implementation of the environment for simulating processes in biogas plants are given, and the specifics of its implementation into the SIMBA#biogas universal system of simulating and simulating the operation of biogas plants are described.

关键词： Software architecture Object oriented modeling Biological system modeling process control Biogas Mathematical models Software Real-time systems Service-oriented architecture Information technology

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