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

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control of Continuous Polymer Synthesis Processes Using Heuristic Optimization Methods

Control of Continuous Polymer Synthesis Processes Using Heur...

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international Russian Smart Industry conference (SmartIndustryCon)

作者： Eldar Miftakhov Sofia Mustafina Dmitry Ivanov Research Department Ufa University of Science and Technology Ufa Russia Department of Mathematical Modeling Ufa University of Science and Technology Ufa Russia Department of Humanities and Natural Sciences Ufa University of Science and Technology Ufa Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

This paper addresses the development of efficient methods for controlling polymer synthesis processes using heuristic optimization techniques. To solve the problem of determining optimal conditions for complex chemical-technological processes, a genetic algorithm is proposed. The key stages of its implementation are defined using modern software development tools. A kinetic modeling approach is presented for evaluating the primary molecular characteristics of polymer products, based on the use of statistical moments of the molecular weight distribution. The application of the genetic algorithm to this process enabled the identification of an optimal two-point control regime, facilitating the production of polymers with desired properties. Computational experiments demonstrated that variations in the mode of regulator feed in conditions of multi-point molecular weight control constitute a significant factor in managing complex processes. This approach provides a basis for planning the molecular parameters of polymer products in the context of continuous production systems.

关键词： Regulators Weight control Process control Optimization methods Production Continuous production Planning Polymers Genetic algorithms Software development management

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Bird’s-Eye-View Trajectory Planning of Multiple Robots using Continuous Deep Reinforcement Learning and Model Predictive control

Bird’s-Eye-View Trajectory Planning of Multiple Robots usin...

引用

IEEE/RSJ international conference on Intelligent Robots and systems (IROS)

作者： Kristian Ceder Ze Zhang Adam Burman Ilya Kuangaliyev Krister Mattsson Gabriel Nyman Arvid Petersén Lukas Wisell Knut Åkesson Chalmers University of Technology Gothenburg Sweden

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Efficient motion planning and control for multiple mobile robots in industrial automation and indoor logistics face challenges such as trajectory generation and collision avoidance in complex environments. We propose a hybrid, sequential method combining Bird’s-Eye-View vision-based continuous Deep Reinforcement Learning (DRL) with Model Predictive control (MPC). DRL generates candidate trajectories in complex environments, while MPC refines these trajectories to ensure adherence to kinematic and dynamic constraints of the robot, as well as constraints modeling humans’ current and predicted future positions. In this study, the DRL utilizes a Deep Deterministic Policy Gradient model for trajectory generation, demonstrating its capability to navigate non-convex obstacles, a task that might pose challenges for MPC. We demonstrate that the proposed hybrid DRL-MPC model performs favorably in handling new scenarios, computational efficiency, time to destination, and adaptability to complex multi-robot situations when compared to pure DRL or pure MPC approaches.

关键词： Adaptation models Trajectory planning Computational modeling Refining Predictive models Deep reinforcement learning Trajectory Planning Collision avoidance Predictive control

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A Method for Rapid Risk Assessment of a Computer Network with a Star-Shaped Topology

A Method for Rapid Risk Assessment of a Computer Network wit...

引用

Information, control, and Communication Technologies (ICCT), international conference on

作者： Alexander Shiroky Laboratory of Complex Systems Security V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The problems of managing the risk of a computer network are often reduced to choosing the optimal set of countermeasures. The influence of their topology on the resulting security level (or the integral risk) is usually not considered because the network topology reflects its functionality and cannot be altered just for security reasons. In addition, such a change could require an inadequate amount of resources. At the same time, understanding the extent and mechanism of topology’s impact on system security could potentially increase the effect of security improvement costs. In this context, it appears beneficial to utilize the findings from examining the impact of complex systems’ structure on their overall risk to address the issue of enhancing computer network security. An earlier study introduced an algorithm aimed at designing a topology to minimize risk within a computer network, and a specific solution for the "bus" topology was presented. In this study, the author introduces a technique for swift risk evaluation of a computer network featuring a star topology.

关键词： Costs Network topology Stars Process control Computer networks Topology Risk management Computer security complex systems Information systems

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Data Pipeline Training: Integrating AutoML to Optimize the Data Flow of Machine Learning Models

Data Pipeline Training: Integrating AutoML to Optimize the D...

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

作者： Jiang Wu Hongbo Wang Chunhe Ni Chenwei Zhang Wenran Lu Computer Science University of Southern California Los Angeles CA USA Computer Science University of Texas at Dallas Richardson TX USA Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA Electrical Engineering University of Texas at Austin Austin TX USA

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Data Pipeline plays an indispensable role in tasks such as modeling machine learning and developing data products. With the increasing diversification and complexity of Data sources, as well as the rapid growth of data volumes, building an efficient Data Pipeline has become crucial for improving work efficiency and solving complex problems. This paper focuses on exploring how to optimize data flow through automated machine learning methods by integrating AutoML with Data Pipeline. We will discuss how to leverage AutoML technology to enhance the intelligence of Data Pipeline, thereby achieving better results in machine learning tasks. By delving into the automation and optimization of Data flows, we uncover key strategies for constructing efficient data pipelines that can adapt to the ever-changing data landscape. This not only accelerates the modeling process but also provides innovative solutions to complex problems, enabling more significant outcomes in increasingly intricate data domains.

关键词： Training Adaptation models Machine learning algorithms control engineering Soft sensors Pipelines Machine learning

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Model-Software complex for Predicting Transport Development 7th

Model-Software Complex for Predicting Transport Development

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7th international conference on Advances in control and Optimization of Dynamical systems (ACODS)

作者： Tsyganov, Vladimir V. Savushkin, Sergey A. Inst Control Sci Moscow 117997 Russia Inst Transport Problems St Petersburg 199178 Russia

Scenarios and forecasts for the development of large socio-economic systems (for example, Russia) are developed regularly. But for the development of transport, more detailed scenarios and forecasts for the development of their transport subsystems (for example, railway transport in Russia) are required. The article discusses the method and technique for solving this problem based on a linear discrete model of the socio-economic system, including its transport subsystem. A model-software complex has been developed for the formation of scenarios and forecasting of the states and indicators of this transport subsystem. This complex gives the possibility to use scenarios and forecasts developed by reputable international and state organizations, regional authorities, as well as large corporations. The results of using this complex concerning the railway transport of Russia show the possibility of forecasting freight traffic on the railways of Russia. (c) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd.

关键词： Transport economics control scenario forecast discrete linear model software

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Estimating NOx Sensor Ammonia Cross-Sensitivity Factor Using a Data-Driven Approach in SCR systems 7

Estimating NOx Sensor Ammonia Cross-Sensitivity Factor Using...

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7th CAA international conference on Vehicular control and Intelligence, CVCI 2023

作者： Wang, Ning Gong, Xun Hu, Yunfeng Sun, Yao State Key Laboratory of Automotive Simulation and Control College of Artificial Intelligence Jilin University Changchun China State Key Laboratory of Automotive Simulation and Control College of Telecommunications Engineering Jilin University Changchun China State Key Laboratory of Automotive Simulation and Control College of Automotive Engineering Jilin University Changchun China

ISBN: (纸本)9798350340488

Selective Catalytic Reduction (SCR) is a module used in the aftertreatment system to mitigate the nitrogen oxides (NOx) emissions, and it can be affected by cross-sensitivity, resulting in a decrease in control performance and even controller failure. A commonly adopted approach is estimating the cross-sensitivity factor to correct the downstream NOx concentration, but the current estimation strategies often incur relatively high costs. In this paper, we propose a novel and more cost-effective method based on data-driven for estimating the cross-sensitivity factor. Specifically, we design a network architecture based on Long Short-Term Memory (LSTM) and attention mechanism. LSTM is utilized to capture the non-linear relationship between input features, historical information, and the cross-sensitivity factor. The introduced attention mechanism allows the model to focus more on important information, thereby further improving the estimation accuracy. This method eliminates the need for complex mechanism modeling and parameter calibration, and reduces the computational burden during online operation, resulting in significant time and computational resource *** simulation experiments conducted transient bench data validate the excellent performance of the designed cross-sensitivity factor estimator, as evidenced by comparative analysis with three alternative methods, and demonstrate the rationality of feature selection through the feature ablation analysis. © 2023 IEEE.

关键词： aftertreatment attention cross-sensitivity factor Long Short-Term Memory

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An Algebraic Structure for Computing Big Data in Livestream

An Algebraic Structure for Computing Big Data in Livestream

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international conference on control, Automation and Information Sciences (ICCAIS)

作者： Dang Van Pham Phan Cong-Vinh Toan Trong Tran Bao Khang Nguyen Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi Vietnam Institute of Applied Mechanics and Informatics Vietnam Academy of Science and Technology Ho Chi Minh City Vietnam Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh City Vietnam British International School Ho Chi Minh City Vietnam

ISBN: (数字)9798331542047

ISBN: (纸本)9798331542054

Nowadays, big data in livestream (BDL) is becoming increasingly prominent in computing systems (CS). Algebraic structures apply algebraic concepts to BDL in CS, aiding in the analysis and resolution of BDL-related problems. This research focuses on algebraic structures related to BDL, such as monoids, to analyze and categorize their properties. These algebraic monoids are essential in formal methods for verifying and analyzing applications of BDL, as they model program behavior and ensure program correctness. This paper examines the algebraic structure of BDL in CS, specifically detailing BDL and formalizing the properties of BDL monoids. Generally, algebraic structures are crucial for computing BDL, offering fundamental frameworks for comprehending and addressing complex issues of BDL in CS.

关键词： Analytical models Automation Computational modeling Big Data

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Image Segmentation Algorithms Composition for Obtaining Accurate Masks of Tomato Leaf Instances 9th

Image Segmentation Algorithms Composition for Obtaining Acc...

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9th Russian Supercomputing Days international conference, RuSCDays 2023

作者： Zhuravlev, Ivan Makarenko, Andrey V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031494345

Large agro-industrial complexes are interested in deep automation of the yields control processes to reduce costs caused by errors or a shortage of qualified personnel. Existing approaches solve problems such as yield assessment or plant pathologies detection, but they cannot properly quantify the volume of plant biomass or the diseased area. One of the reasons for this limitation is the poor quality of masks of object instances formed in machine vision systems. This occurs because of Mask R-CNN architecture, which is usually used in the computer vision. In this paper, we propose an algorithms composition for obtaining accurate masks of objects in task of segmentation of tomato leaf instances in images collected in difficult conditions of industrial greenhouses. The use of Mask R-CNN combined with CascadePSP neural network algorithm increased the average IoU by 1.194% compared to "pure" Mask R-CNN on images with complex object-like background. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer vision

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Identification of nonlinear systems in the frequency domain using two-dimensional Volterra series

Identification of nonlinear systems in the frequency domain ...

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international conference on control, Instrumentation, and Automation

作者： Masoud Soheili Mohsen Shafieirad Tahereh Morovati Erfan Kouhi Ronaghi Department of Electrical and Computer Engineering University of Kashan Kashan Iran Department of Electrical Engineering Iran University of Science and Technology Tehran Iran Department of Electrical and Electronic Engineering Shahed University Tehran Iran

ISBN: (数字)9798331509972

ISBN: (纸本)9798331509989

This paper presents the identification of second-order two-dimensional kernels using the Volterra series model in the frequency domain. The study focuses on nonlinear systems where the input varies over both time and spatial dimensions. The Volterra series, known for its effectiveness in modeling complex nonlinear systems, is extended to two dimensions. The kernels are computed using the least squares method, with the input defined as a product of cosine functions. By simplifying the expressions and applying the Fourier transform, accurate kernel identification is achieved. The results demonstrate the efficacy of this approach in precisely matching the estimated system with the actual system, as evidenced by the minimal identification error. This work contributes to the development of advanced techniques for nonlinear system identification in industrial and scientific applications.

关键词： Accuracy Frequency-domain analysis Computational modeling Instruments Refining Process control Nonlinear dynamical systems Nonlinear systems Kernel Least mean squares methods

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AUV With Additional Thruster Stabilization System to Perform Contact Manipulation Operations

AUV With Additional Thruster Stabilization System to Perform...

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2023 international conference on Ocean Studies, ICOS 2023

作者： Konoplin, Alexander Krasavin, Nikita Vasilenko, Roman Academician M. D. Ageev Institute of Marine Technology Problems Far Eastern Branch of Ras Vladivostok Russia

ISBN: (纸本)9798350382457

The paper describes a synthesis method of automatic hover mode stabilization systems of interventional autonomous underwater vehicles (I-AUV) equipped with an additional rotatable thruster. This thruster is installed on the same axis of rotation with the first joint of the underwater manipulator (UM) above the center of the I-AUV buoyancy on an outrigger rod mounted on a rotary platform. Additional thruster expands the I-AUV initial propulsion and steering complex (PSC). Changing the direction and magnitude of this thruster's thrust vector provides effective compensation for arbitrary force and torque effects from the UM, which lead to undesirable roll and pitch displacements of the I-A UV. At the same time the additional thruster force effects, which lead to undesirable linear I-AUV displacements, are compensated by the march and steering thrusters thrusts of the initial PSC. These thrusts are created in real time. As a result, it is possible to stabilize the I-AUV in the desired spatial position during the contact manipulation operations with underwater objects. At the same time, a thrust is provided at the mounting point of the UM. It's necessary so that the UM end effector (EE) exerts a given force on the work object surface. The operability and efficiency of the synthesized I-AUV stabilization system while performing contact manipulation operations are confirmed by the results of numerical modeling in Matlab/Simulink with visualization in the CoppeliaSim simulator. © 2023 IEEE.

关键词： Autonomous underwater vehicles

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