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2024 international conference on Information Science and Communications Technologies, ICISCT 2024

作者： Maxamadjanovna, Umurzakova Dilnoza Mirzaolimovich, Sobirov Muzaffar Qizi, Abdullayeva Mohigul Rahimjon Fergana Branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Department of Information Technologies Fergana Uzbekistan

ISBN: (纸本)9798331527921

The article presents a method of integrating control systems in heat and power applications with distributed parameters using matrix polynomial models. They speak about the consideration of complex phenomena such as heat exchange and conduction for introducing the improvement in control. It also allows achieving better modeling of the system's behavior while maintaining stability and minimizing transients. The work also builds the approach converting systems of equations into matrix polynomial ones that helps perform computational analysis and synthesis of controllers. By simulation modeling, the efficiency of this method is proved, showing that it is equally suitable to cope with external interferences as well as increase the degree of control precision. The consequences of the study suggest that matrix polynomial models will enhance the effective control of thermal power facilities as it minimizes energy losses. © 2024 IEEE.

关键词： control system synthesis

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Space vector modulation direct torque control of high speed permanent magnet synchronous motor based on five-level inverter 25

Space vector modulation direct torque control of high speed ...

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25th international conference on Electrical Machines and systems (ICEMS)

作者： Li, Jiaxi Jin, Shi Zhang, Fengge Wang, Huijun Liu, Bing Yin, Chao Shenyang Univ Technol Sch Elect Engn Shenyang Peoples R China Beihang Univ Beijing Peoples R China Shandong Bocheng Elect Co Ltd Jinan 273512 Shandong Peoples R China

ISBN: (纸本)9781665493024

Due to the unique electromagnetic design of highspeed Permanent Magnet Synchronous Motor (HPMSM), the stator inductance value is small, which will cause problems such as stator current harmonics and excessive torque ripple in operation. Multilevel inverter can produce more levels and make the output voltage of inverter closer to sine wave. Direct Torque control (DTC) has the advantages of simple algorithm and fast response, and is widely used in the control system of high-speed PMSM. However, multilevel inverters have many vectors and complex algorithms. Therefore, this paper proposes a simplified five-level Space Vector Pulse Width Modulation (SVPWM) algorithm and applies it to Space Vector Modulated Direct Torque control (SVM-DTC). The proposed SVM-DTC strategy based on simplified five-level SVPWM can effectively reduce the calculation amount and reduce the harmonic content of stator current and torque ripple, so that the motor drive has good steady state and dynamic performance. The proposed method is simulated in MATLAB/SIMULINK software, and compared and analyzed with the three-level SVM-DTC system. This method can inhibit the harmonic content of stator current and torque ripple obviously.

关键词： PMSM Five-level inverter DTC SVM-DTC

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Vertical Crossing Tracking control of Water-Air Amphibious Buoys on Wave Surfaces

Vertical Crossing Tracking Control of Water-Air Amphibious B...

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2024 international conference on Guidance, Navigation and control

作者： Yang, Ling Lu, Mingqing Liao, Fei Shao, Zhijiang Zhejiang Univ Coll Control Sci & Engn Hangzhou 310013 Peoples R China Aerodynam Res & Dev Ctr Mianyang 621000 Sichuan Peoples R China Harbin Engn Univ Sci & Technol Underwater Vehicle Lab Harbin 150001 Peoples R China

ISBN: (纸本)9789819622702;9789819622689;9789819622672

Nonlinear control strategy is designed to address the problem of modeling uncertainty and complex external environmental interference in crossing water and air media for amphibious buoys. This controller consists of an adaptive backstepping controller and a disturbance observer. Firstly, the medium crossing mechanism of the coaxial water air cross domain flying buoy studied in this article is analyzed and modeled, fully considering some additional variables such as water resistance, buoyancy and its corresponding torque, as well as wave loads. A continuous dynamic model is established by designing a smooth transition function. The backstepping controller forms the foundation of the controller, and the disturbance observer enhances the robustness of the closed-loop system by estimating the lumped uncertainty that is difficult to measure. Meanwhile, an adaptive algorithm is introduced to compensate for the remaining residuals of the disturbance observer. The combination of adaptive algorithms and disturbance observers improves the robustness of the system. The stability of closed-loop systems is proven using Lyapunov functions. Finally, Simulink simulation is conducted on the proposed controller, and the results show that even in the presence of disturbances and uncertainties, the designed controller has strong suppression ability against unknown disturbances, effectively demonstrating the superiority and robustness of the proposed method.

关键词： Vertical Crossing Amphibious Buoys Tracking control Adaptive Backstepping controller Disturbance Observer

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Access control Attribute Mining Model Based on ALBERT-PFN

Access Control Attribute Mining Model Based on ALBERT-PFN

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Cognitive Computing and complex Data (ICCD), international conference on the

作者： Zhaoxiong Bu Li Ma Jihui Li Linjiu Guo Yong Zhong Zhongrong Zeng Foshan University Foshan China Guangdong Strong Metal Technology Co. Ltd Foshan China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

In the evolving field of cybersecurity, efficiently managing Attribute-Based Access control (ABAC) remains crucial due to complex attribute relationships. This paper introduces the ALBERT-PFN model, a novel access control attribute mining approach that employs deep learning to transform ABAC challenges into joint entity and relationship extraction tasks. The model leverages ALBERT for contextual word embeddings and a Positional Feature Network (PFN) that dynamically interprets relationships between entities, significantly enhancing both the accuracy and automation of attribute mining. Experimental results show that ALBERT-PFN achieves a precision of 88.13%, a recall of 91.80%, and an F1 score of 89.93% in entity recognition, outperforming existing methods. In relationship extraction, it further excels with a precision of 81.55%, a recall of 72.94%, and an F1 score of 77.01%, underscoring its effectiveness in developing dynamic and precise ABAC policies.

关键词： Access control Deep learning Computational modeling Transforms Feature extraction Data models Data mining Computer security Cognitive systems Context modeling

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Research On Line Of Sight Motion modeling And Fire control Correction Of Ballistic Calculation System

Research On Line Of Sight Motion Modeling And Fire Control C...

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2022 CSAA/IET international conference on Aircraft Utility systems, AUS 2022

作者： Shen, Cheng Fan, Shixun Chen, Yukang Zhu, Wenliang Zhang, Lianchao Fan, Dapeng College of Intelligence Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

In order to reduce the preparation time and improve the accuracy of shooting, an ultralight and multiple light weapons reusable ballistic calculation system and fire control correction method were proposed. Based on the analysis of human gun-aiming-firing, the basic modules of fire control elements calculation, real-time environment perception, multi-light weapons reuse, interaction and data management are planned. A fire control correction software architecture based on domestic calculation platform is proposed, which can be solved quickly and in real time. A nonlinear extend Kalman filter is proposed to solve the problems of graphic display lag, firing device delay and sensor noise. In order to verify the effectiveness, a 600-meter field shooting test was set up for simulation analysis and experimental test. The results show that the system can make the novice learn shooting essentials quickly and improve the long-distance shooting ability after a short training. © 2022 IET conference Proceedings. All rights reserved.

关键词： Ballistics

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A Smart Decision Making System for the Selection of Production Parameters using Digital Twin and Ontologies

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international JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第2期13卷 408-420页

作者： Abadi, Mohammed Abadi, Chaimae Abadi, Asmae Ben-Azza, Hussain Moulay Ismail Univ Ecole Natl Super Arts & Metiers ENSAM Meknes Informat Proc & Control Syst MTICS Team Lab Mech Mechatron & Command Modeling BP 4042 Meknes 50000 Morocco Moulay Ismail Univ Lab Mech Mechatron & Command Elect Power Maintenance & Innovat Team Ecole Natl Super Arts & Metiers ENSAM Meknes BP 4042 Meknes 50000 Morocco Euromediterranean Univ Fez INSA Fes Morocco

Currently, the industrial and economic environment is highly competitive, forcing companies to keep up with technological progress and to be efficient in terms of quality and responsiveness, not only to survive, but also to dominate the market. So, to achieve this goal, companies are always looking to master their production processes, as well as to enlarge their range of products, either by developing new products or by improving old ones. This confronts companies to many problems, including the identification of adequate and optimal production parameters for the development of their products. In this context, a decision making system based on digital twins (DT), case-based reasoning (CBR) and Ontologies is proposed. The originality of this work lies in the fact that it combines three emerging artificial intelligence tools for modeling, reasoning and decision making. Thus, this work proposes a new flexible and automated system that ensures an optimal selection of production parameters for a given complex product. An industrial case of study is developed to illustrate the effectiveness of the proposed approach.

关键词： Production parameters selection digital twin case-based reasoning ontologies automation cyber-physical systems decision making artificial intelligence

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Models of Battle Dynamics in Strategic Computer Games

Models of Battle Dynamics in Strategic Computer Games

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international conference on Management of Large-Scale System Development (MLSD)

作者： Ivan Dmitrievich Laryushin Dmitrii Sergeevich Pashin Yaroslav Alekseevich Koltochenko Felix Ivanovich Ereshko Plasma Physics Department Gaponov-Grekhov Institute of Applied Physics RAS Nizhny Novgorod Russia Faculty of Physics National Research Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Department of Mathematical Modeling of Complex Systems and Optimization Moscow Institute of Physics and Technology Moscow Russia Department of Information and Computing Systems Federal Research Center "Computer Science and Control" of the RAS Moscow Russia

A set of new models that describe the dynamics of battles in strategic computer games is presented. These models not only have descriptive functions, but also allow solving problems of optimizing army control under given conditions, as well as calculating the most efficient composition of the army for the planned operation within a computer game.

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A Review of Deep Reinforcement Learning Exploration Methods: Prospects and Challenges for Application to Robot Attitude control Tasks 7th

A Review of Deep Reinforcement Learning Exploration Methods...

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7th international conference on Cognitive systems and Information Processing, ICCSIP 2022

作者： Li, Chao Wu, Fengge Zhao, Junsuo University of Chinese Academy of Sciences Beijing China Beijing China

ISBN: (纸本)9789819906161

In recent years, deep reinforcement learning has been widely used in the real world, such as in robot control and autonomous driving. However, the sample-inefficient of deep reinforcement learning prevents its application in robot control. In addition, complex real-world scenarios require the high robustness of robot controllers, and the design of controllers needs to consider the influence of the external environment. These problems become severer in environments with high-dimensional state action spaces and sparse delay rewards. In this paper, we provide a systematic introduction and summary of the existing methods for exploration. Firstly, we introduce the primary exploration techniques and summarize the challenges faced by intelligent body exploration. Then, we classify the existing exploration methods in terms of whether they generate other bonuses or not and elaborate on the ideas of different methods. Finally, we discuss the challenges of applying deep reinforcement learning to robot control and the applicability of different exploration methods to attitude control tasks, ruling out exploration methods unsuitable for attitude control tasks for subsequent research. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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Utilizing Deep Convolutional Neural Networks for Image-Based Plant Disease Detection 1

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7th international conference on Inventive systems and control, ICISC 2023

作者： Reno, Saha Turna, Marzia Khan Tasfia, Sheikh Abir, Md. Aziz, Anusha Bangladesh Army International University of Science and Technology Cumilla Bangladesh Military Institute of Science and Technology Dhaka Bangladesh University of Erlangen Nuremberg Erlangen and Nuremberg Bavaria Germany Bangladesh University of Business and Technology Dhaka Bangladesh

ISBN: (数字)9789819916245

ISBN: (纸本)9789819916238

Automatic leaf disease detection is a challenging problem in smart agriculture due to the variations in appearance and the complicated backgrounds of plant diseases. Designing a deep convolutional neural network model that extracts visual illness features from the photos and then recognizes the diseases based on the retrieved features is a standard solution to this problem. This method works well when the background is simple, but it has poor accuracy and robustness when the background is complex. The primary factor in identifying leaf-based plant diseases is the color information of sick leaves. Most existing approaches for diagnosing plant diseases depend on the expert diagnosis, which inevitably results in field management and crop disease control behind the times. In this paper, our methodology is based on deep CNN which can be applied to solve these problems to improve the speed and accuracy of disease classification and recognition of plant diseases. We mainly focus on a deep CNN-based model with fine-tuning vegetable leaf diseases dataset. Transfer learning models implemented with famous pre-trained models such as VGG-16 and ResNet-50 are compared with our proposed model. Our proposed model outperforms various existing solutions with an Mean Average Precision (mAP) accuracy of 99.80%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object detection

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Dynamic Response Characteristics and control Strategies of Mechanical systems

Dynamic Response Characteristics and Control Strategies of M...

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Power, Electrical Engineering, Electronics and control (PEEEC), international conference on

作者： Guiping Xie Jian Fan Heping Jia Guili Xie Erdos Vocational College of Eco-Environment Erdos Inner Mongolia China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378924

Compared to the mature research and application of static optimization technology, dynamic response optimization has always been a research hotspot and difficulty in the field of system optimization design due to its complex dynamic constraints and variable environmental factors. As an indispensable key component in modern engineering, mechanical systems (MS) have dynamic behavior characteristics that are directly related to the overall performance stability, response speed, and working accuracy of the system. This is particularly prominent in complex and ever-changing working environments. This article focuses on the dynamic response characteristics and control strategies of MS. Through a combination of theoretical analysis and experimental verification, the dynamic response laws of MS under different working conditions are systematically studied, and corresponding optimization control strategies are proposed. The experimental results show that the control strategy proposed in this article can effectively address the dynamic challenges of MS in complex working environments, significantly reduce vibration levels, improve system response speed, and enhance the overall stability and reliability of the system. This provides strong theoretical support and practical methods for optimization design and control practice in related fields.

关键词： Dynamic response Vibrations Employee welfare Computational modeling Reliability theory Aerodynamics Stability analysis Mechanical systems Optimization Thermal stability

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