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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

共 12282 条记录，以下是1521-1530 订阅

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Analysis of Oscillations in Nonlinear Human-Operated Robotic System

Analysis of Oscillations in Nonlinear Human-Operated Robotic...

引用

international Russian Smart Industry conference (SmartIndustryCon)

作者： Boris Andrievsky Nikolay V. Kuznetsov Iuliia Zaitceva dep. Control of Complex Systems Institute of Problems in Mechanical Engineering of RAS dept. Applied Cybernetics St. Petersburg State University St. Petersburg Russia dep. Information and Control Systems Institute of Problems in Mechanical Engineering of RAS

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The development of automation is characterized by the increasing complexity of control tasks associated with various technical objects. However, this does not exclude the human element from the control process. Manual control has certain drawbacks that negatively impact the quality of management, primarily arising from the interaction between the operator and the nonlinear dynamics of the robot. This study examines a manual control system for a robotic manipulator, taking into account nonlinear constraints that may manifest as limitations on the power of the actuating mechanism or as part of a local regulator. The parameters of the operator's control actions exhibit a certain range due to individual characteristics of the human operator or the control technique employed. Additionally, signal transmission delays may be present in the control loop. Considering these system characteristics provides a more comprehensive understanding of control quality and allows for the establishment of acceptable control techniques for the human operator. Depending on the frequency of input disturbances, this work analyzes the closed-loop system comprising the operator and manipulator using methods based on harmonic linearization of nonlinearity and harmonic balance equations: locus of a perturbed relay system and harmonic stabilization. The results of calculations and simulations using these methods indicate that there exists a parameter space within which oscillations may arise. Thus, when designing manual control systems for robotic manipulators, it is essential to pay attention to the control techniques employed by the human operator and to overall delays in order to avoid undesirable operational modes of the system.

关键词： Training Service robots System performance Human factors Harmonic analysis Mathematical models Delays Relays Oscillators Remote control

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On Some Properties of Padé Approximations for Fractional Order Transfer Function (FOTF)

On Some Properties of Padé Approximations for Fractional Or...

引用

international conference on Methods and Models in Automation and Robotics (MMAR)

作者： Jacek Jagodziński Marta Lampasiak Department of Control Systems and Mechatronics Wrocław University of Science and Technology Wrocław Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

The issue of identifying and designing control systems of fractional order models involves the necessity of their approximation to integer order. The most popular techniques include: Oustaloup’s method, Matsuda’s method, CFE (Continued Fraction Expansion) method, M-SBL method and different more. It is also possible to use the Padé approximation. The article examines some properties of this method. The case of the fractional power term (complex variable transfer function raised to a fractional power) is the main focus since it serves as a basis for approximating more intricate fractional order systems. The article’s innovation is in using the nonlinear least squares method to obtain a mathematical description of the behavior of the zeros and poles of the chosen component after approximation. Relying on the gathered statistics, it was found that a very good fit was produced. The approximation of the behaviour of zeros and poles also allowed for the presentation of a new, alternative notation for the Padé approximation.

关键词： Technological innovation Computational modeling Writing Approximation algorithms control systems Stability analysis Poles and zeros

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DRCI: A Developer Recommendation Method for Issues Using Comprehensive Information

DRCI: A Developer Recommendation Method for Issues Using Com...

引用

Advanced Algorithms and control Engineering (ICAACE), international conference on

作者： Jie Zhou Tao Wang State Key Laboratory of Complex&Critical Software Environment College of Computer Science and Technology National University of Defense Technology Changsha Hunan Province China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

With the rapid development of Open Source Software (OSS), open-source platforms represented by GitHub have become the core hub for global developer collaboration and innovation. However, the explosive growth of open-source projects, especially the surge in the number of issues, has posed challenges for developers. On one hand, developers face the problem of information overload when selecting issues to make contributions; on the other hand, maintainers are confronted with the difficulty of finding efficient and rational issue assignment methods to achieve effective issue resolution. To address these challenges, researchers have proposed various methods for recommending developers for issues. However, existing studies have the following limitations: (1) Single information utilization; (2) Insufficient dynamic modeling; (3) Lack of the impact of developer inactivity periods. To tackle these problems, this paper proposes a developer recommendation method DRCI that integrates multidimensional information. By modeling developers' preferences for issue attributes over time and leveraging KGCN for data information mining, DRCI significantly enhances the recommendation performance, providing a more efficient solution for issue management in open-source communities.

关键词： Hands Technological innovation control engineering Explosives Data models Data mining Surges Open source software Faces Software development management

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modeling and Simulation Design of Single Crystal Silicon Growth by Czochralski Method

Modeling and Simulation Design of Single Crystal Silicon Gro...

引用

Mechatronics Technology and Intelligent Manufacturing (ICMTIM), international conference on

作者： Ruidong Xie Wenle Ma Zheqi Zhang Pei Zhu Yingmin Yi Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9798350363265

ISBN: (纸本)9798350363272

Due to difficulties in observing crystal state and the high cost of crystal preparation, the teaching of the Czochralski single crystal silicon production is complex. To solve the above problem, a digital twins-inspired virtual simulation system for the growth of single crystal silicon was developed. The 3D models of the single crystal furnace, single crystal silicon rods, and other related objects were created using Blender. The nonlinear model of the single crystal silicon growth process was established based on the heat conduction during crystal growth and geometric deformation. The 3D models were then imported into the web page using ***. The PID control algorithm was used to control the temperature and pulling speed, and finally, the B/S architecture was adopted to design and implement the virtual simulation experiment system for the growth of Czochralski single crystal silicon. The virtual simulation method will help to overcome the shortcomings of on-site experiment teaching and enhance students’ understanding of the entire single crystal silicon preparation process.

关键词： Crystal growth Heating systems Solid modeling Three-dimensional displays PI control Furnaces Education

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Traffic Network modeling and Volume control Using Labeled Petri Nets

Traffic Network Modeling and Volume Control Using Labeled Pe...

引用

IEEE Intelligent Transportation systems conference (ITSC)

作者： Ruan, Keyu Li, Lingxi Indiana Univ Purdue Univ Purdue Sch Engn & Technol Transportat & Autonomous Syst Inst TASI Indianapolis IN 46202 USA Indiana Univ Purdue Univ Purdue Sch Engn & Technol Dept Elect & Comp Engn Indianapolis IN 46202 USA

ISBN: (纸本)9781728191423

Traffic planning and estimation are critical tasks in the management of complex road networks. With appropriate control strategies, traffic congestion can be significantly alleviated. In this paper, we propose approaches for estimating the traffic flow and vehicle distributions based on labeled Petri nets. The traffic network is firstly modeled as a labeled Petri net structure, then the control algorithms are introduced. Different from many existing strategies that focus on avoiding collisions, we assign traffic capacities to places that represent different road segments in the traffic network, then algorithms are developed to maintain the number of tokens within given capacities. The existence of the unobservable transitions makes the problem more challenging. Under some assumptions of the unobservable transitions, we show that the proposed algorithm is efficient and has a complexity that is polynomial in the length of the label observations. An illustrative example is also provided to show the effectiveness of the proposed algorithm.

关键词： Solid modeling Roads conferences Petri nets Estimation Planning complexity theory

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A Novel Hybrid Approach for Detecting Abnormal Vessel Behavior in Maritime Traffic 7

A Novel Hybrid Approach for Detecting Abnormal Vessel Behavi...

引用

7th IEEE international conference on Transportation Information and Safety, ICTIS 2023

作者： Li, Jiamin Liu, Jin Zhang, Xiliang Li, Xingye Wang, Junxiang Wu, Zhongdai Shanghai Maritime University College of Information Engineering Shanghai China Cosco Shipping Technology Co. Ltd National Engineering Research Center of Ship Transportation Control Systems Shanghai China Shanghai Ship and Shipping Research Institute State Key Laboratory of Maritime Technology and Safety Shanghai China

ISBN: (纸本)9798350308532

The Abnormal Behavior Detection of Vessels (ABVD) is crucial for enhancing Vessels' situational awareness as well as achieving effective management of maritime traffic. Clustering algorithms are extensively employed for ABVD tasks, however, they are not only time-consuming but also frequently inaccurate when dealing with complex and dynamic vessel trajectory detection tasks. To address the above problems, we propose a novel hybrid approach, CSDLSTM(Course/Speed-DBSCAN and LSTM), which combines Density-based Clustering(DBSCAN) and long short-term memory networks to improve the efficiency of ABVD. Specifically, a three-dimensional CS-DBSCAN (Course/Speed-DBSCAN) algorithm is proposed, which incorporates speed and course features along with geospatial information in the clustering process to accurately describe vessel behavior. In addition, the clustering results are used as traffic patterns to train the LSTM predictor for real-time maritime anomaly detection. Experiments conducted on real AIS datasets demonstrate that the CSD-LSTM method has greater precision and efficiency in ABVD. © 2023 IEEE.

关键词： Efficiency

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Research on Multivariable control of Boilers Based on Model Predictive control (MPC) and Genetic Algorithm

Research on Multivariable Control of Boilers Based on Model ...

引用

Advanced Algorithms and control Engineering (ICAACE), international conference on

作者： Jiale Wang School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

This paper proposes a model predictive control (MPC) method based on genetic algorithm optimization for the problem of multivariable control of boilers. By constructing a dynamic mathematical model and an optimization control strategy for the boiler system, the problems of high energy consumption, slow response and insufficient anti-interference in traditional control methods are solved. In the experimental design, a comparative analysis of traditional MPC and GA-MPC was conducted in combination with a dynamic simulation platform. The results show that GA-MPC is significantly superior to traditional MPC in steady-state energy consumption optimization, can effectively reduce energy consumption by about 28.5%, and maintain good control accuracy and rapid response capabilities in the dynamic adjustment stage. At the same time, GA-MPC shows higher robustness and stability when dealing with complex multivariable systems, proving that the global optimization capability of genetic algorithms significantly improves the performance of MPC. The research results of this paper provide an efficient optimization strategy for boiler control systems, which has important theoretical value and engineering application significance.

关键词： Energy consumption Heuristic algorithms Boilers Prediction algorithms Stability analysis Robustness Steady-state Optimization Genetic algorithms Predictive control

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PMSM System Identification by Knowledge-informed Machine Learning

PMSM System Identification by Knowledge-informed Machine Lea...

引用

IEEE international conference on Industrial Informatics (INDIN)

作者： Yue Yu Jiageng Tong Jinhui Xia Jinya Su Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Because of its excellent efficiency, compact dimen-sions, and accurate control features, Permanent Magnet Syn-chronous Motor (PMSM) are experiencing widespread applications across various industries. By accurately characterizing the dynamic behavior of PMSM systems through system identi-fication, engineers can ensure that PMSM motors reach their maximum potentials and meet the stringent requirements of modern industrial and technical systems while reducing energy consumption and maintenance costs. The traditional recursive least squares method is sensitive to noises, and unable to accu-rately identify parameters in complex environments. Pure data-driven models lack interpretability and require complex model architecture and computational costs. To this end, this work draws knowledge-informed neural ordinary differential equations (NODEs) for system identification, which embeds system prior knowledge into the NODEs for more efficient and accurate model learning. Comparative simulations show that this method not only obtains a higher-precision system model, but also significantly reduces the amount of training data and computation costs.

关键词： Accuracy Costs Uncertainty Computational modeling Noise Ordinary differential equations Motors Mathematical models Data models System identification

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Stability Analysis and Improvement of Symmetric PLL-Based VSC in Weak Grids

Stability Analysis and Improvement of Symmetric PLL-Based VS...

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Electrical Energy Conversion systems and control（IEECSC), IEEE international conference on

作者： Xiaohui Jiang Shuying Yang Zhanpeng Cai Nan Yao School of Electrical Engineering and Autimation Hefei University of Technology Hefei China

ISBN: (数字)9798350389357

ISBN: (纸本)9798350389364

For grid-connected voltage source converter (VSC) under weak grid conditions, frequency coupling caused by asymmetric system structure poses challenges for system modeling and controller design. Fortunately, frequency coupling can be eliminated by introducing a symmetrical Phase-locked loop (SPLL). Meanwhile, the employed SPLL can symmetrize the system model, transforming the complex multi-input multi-output (MIMO) system into a simpler single-input single-output (SISO) system. This paper derives an impedance model of grid-connected inverters with a symmetrical Phase-Locked Loop (SPLL). Analysis of the impedance characteristic using the impedance model established shows that the symmetrical PLL has a significant negative impact on system stability in weak grid. Moreover, a novel grid voltage feed-forward strategy is proposed to improve the stability of VSC under weak grid conditions. The effectiveness of the strategy has been validated through simulations.

关键词： Couplings Analytical models Adaptation models Power system stability control systems Stability analysis Impedance Phase locked loops Voltage control Voltage-source converters

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Uncertainty-Aware Voltage control for Distribution Substations Based on Bayesian Deep Learning and Probabilistic Graph Self-Encoder Fusion

Uncertainty-Aware Voltage Control for Distribution Substatio...

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Intelligent Power and systems (ICIPS), international conference on

作者： Jun Wei Jiong Ma Jian Hu Fei Zhu Hangzhou Electric Power Design Institute Co. Ltd. Hangzhou China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

Voltage control in low-observable distribution networks faces significant uncertainty challenges. In this paper, an uncertainty-aware voltage control method based on the fusion of Bayesian deep learning and probabilistic graph self-encoder is proposed. The method first utilizes Bayesian deep learning to establish a probabilistic model of the network topology and inter-node dependencies, and then realizes efficient encoding and decoding of the system state through a probabilistic graph self-encoder. This fusion approach combines the uncertainty quantification capability of Bayesian inference and the structure learning advantage of graph self-encoders to achieve multi-scale uncertainty modeling and dynamic decision optimization. Specifically, this paper develops a Bayesian deep learning model augmented by graph attention network to effectively capture the complex topology of the network; meanwhile, an adaptive conditional probabilistic generative adversarial network is proposed to generate realistic and diverse probabilistic scenarios. By fusing these two techniques, this method achieves adaptive probabilistic scenario generation and screening, as well as uncertainty-based dynamic control strategy optimization. Experimental results show that the fusion method significantly improves the robustness and adaptability of voltage control in low-observable distribution networks, and provides a new idea for solving the uncertainty problem of complex distribution systems.

关键词： Deep learning Adaptation models Uncertainty Network topology Distribution networks Probabilistic logic Data models Bayes methods Voltage control Optimization

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