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1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022

作者： Kurashkin, Sergei Tynchenko, Vadim Myrugin, Aleksander Bocharov, Aleksey Seregin, Yuriy Tynchenko, Yadviga Information Control Systems Department Reshetnev Siberian State University of Science and Technology Siberian Federal University Laboratory of Biofuel Compositions Krasnoyarsk Russia Bauman Moscow State Technical University Digital Material Science: New Materials and Technologie Krasnoyarsk Russia Siberian Federal University Department of Technological Machines and Equipment for Oil and Gas Complex Krasnoyarsk Russia

ISBN: (数字)9781665443579

ISBN: (纸本)9781665443579

In the aerospace industry, induction brazing in various environments is widely used, for example, low-temperature brazing, brazing in protective environments, but the classical method of connecting waveguide paths (pipe-flange-pipe) is not inferior to them. However, induction heating is a very complex research process, which continues to this day. In this work, the authors have proposed a mathematical apparatus based on thermal processes during verification. A stationary continuously operating source of heat is considered, considering the equalization of temperatures, since the rate of heating of the solder and flux at the junction of the pipeline and the flange has a huge influence on the formation of the penetration channel. Also, the authors propose the use of regression analysis to restore the values of technological parameters. Thus, the approach used will allow considering the change in thermophysical parameters in the process of induction heating, which will increase the accuracy of the results obtained. The Russian development SimInTech is used as a modeling tool. The application of the approach proposed in the article can significantly reduce labor and material costs for the development of the technological process of induction soldering of waveguide paths both when correcting existing processes and when introducing new standard sizes and materials of products into production. © 2022 IEEE.

关键词： Induction heating

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Decomposition of skin-friction and heat flux in compressible transitional channel flows simulated by direct and constrained large-eddy simulations

Decomposition of skin-friction and heat flux in compressible...

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第十二届全国流体力学学术会议

作者： Sanmu Chen Dehao Xu Minping Wan Shiyi Chen Department of Mechanics and Aerospace Engineering Southern University of Science and Technology State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University

Direct and constrained large-eddy simulations(CLES) of the temporal transition in a compressible channel flow are performed. First, we confirm that the CLES with an intermittency factor can accurately predict the transition onset, and its accuracy is greatly improved compared with the traditional dynamic Smagorinsky model(DSM). However, both the friction and heat flux maxima predicted by CLES are smaller than the results from DNS. We then decompose the friction and heat flux using the two-fold integration method with DNS and CLES results respectively, showing that the transition process can be divided into two stages, an early transition stage and a late transition stage dominated by Reynolds turbulent stress term and mean velocity gradient term respectively, and the variation of mean velocity profile gradient term contributes most for this difference. This is of great significance to further improve the CLES method so that it can accurately predict the process of transition and the maximum value of friction and heat flux.

关键词： CLES transition predict skin-friction decomposition

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Distributed State and Fault Fusion Filtering for Nonlinear systems Subject to Quantization Effects

Distributed State and Fault Fusion Filtering for Nonlinear S...

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IEEE International Conference on Control science and systems Engineering (CCSSE)

作者： Zhibin Hu Jun Hu Junhua Du Yuna Zhao Department of Mathematics Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology Harbin China

In this paper, the distributed state and fault fusion filtering problem is discussed for a class of multi-sensor networked systems (MSNSs) with randomly occurring quantized measurements (ROQMs). A series of random variables obeying the Bernoulli distribution are adopted to depict the phenomenon of the ROQMs and the fault signal is assumed to appear with an unknown constant type. The aim of this paper is to provide the state and fault fusion filtering algorithm by using the inverse covariance intersection fusion method. Moreover, a proper filter gain is designed by minimizing the local upper bound of filtering error covariance. Finally, the effectiveness of the presented fusion method is verified by using an illustrative example.

关键词： Upper bound Quantization (signal) Filtering Filtering algorithms systems engineering and theory Numerical simulation Control systems

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Tan, Qingshan Li, Changhe Zeng, Sanyou Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9798350314588

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front. © 2023 IEEE.

关键词： Multiobjective optimization

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Software System for Modeling Temperature Distribution During the Electron Beam Welding 4

Software System for Modeling Temperature Distribution During...

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4th IEEE International Conference on Design and Test of Integrated Micro and Nano-systems, DTS 2022

作者： Rogova, Daria Kurashkin, Sergei Tynchenko, Vadim Shutkina, Elizaveta Saidov, Nazar Bocharov, Aleksey Reshetnev Siberian State University of Science and Technology Information Control Systems Department Krasnoyarsk Russia Laboratory of Biofuel Compositions Siberian Federal University Russia Digital Material Science: New Materials and Technologie Bauman Moscow State Technical University Krasnoyarsk Russia Siberian Federal University Department of Technological Machines and Equipment for Oil and Gas Complex Russia

ISBN: (纸本)9781665497831

Now, electron beam welding (EBW) has become widespread in the manufacture of aerospace products. However, to achieve a stable quality of the weld and the required geometric dimensions, it is necessary to set the appropriate technological parameters, which causes difficulties when commissioning a new product from another alloy or purchasing welding equipment (in particular, an electron beam welding equipment;an electron beam gun with a different accelerating voltage from used). At the same time, there are the following most common technological problems that are encountered in the production of thin-walled structures for aerospace purposes: (1) root defects;(2) the absence of computational models of the EBW process. The authors of this work propose to develop a software system that will allow: (1) to simulate the process of electron beam welding for almost any products and alloys, which will make it possible to determine the optimal technological parameters and, therefore, prevent root defects;(2) to simplify the EBW modeling process, in comparison with such systems as MATLAB, ANSYS and Comsol, in which the EBW modeling process is complicated by the features of these programs, the requirements for knowledge of calculation models, the ability to program them and the creation of a product sketch in CAD systems. The software system proposed by the authors will make it possible to simplify the modeling process, reduce the time of modeling the EBW process, considering the thermophysical and geometric characteristics of the product, store both the results of the developed technological process and the simulation results. Thus, the software system developed by the authors for modeling the temperature distribution in the process of electron beam welding will prevent the technological problems encountered in production and obtain a stable quality of the weld in the process of electron beam welding. © 2022 IEEE.

关键词： Electron beam welding

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Prediction Method of Truck Travel Time in Open Pit Mines Based on LSTM Model 42

Prediction Method of Truck Travel Time in Open Pit Mines Bas...

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42nd Chinese Control Conference, CCC 2023

作者： Ao, Mengting Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9789887581543

Aiming at the prediction of truck travel time in open pit mines, we established a prediction model based on long short-term memory(LSTM). This model fully accounts for 11 factors, including the nature of trucks, weather, road conditions, and driver's behaviors, as well as the influence of neighbor road segments in the route on the current predicted road segment. The experiment shows that the error of the LSTM prediction model is significantly reduced compared with SVR and BP models. In addition, the maximum absolute mean error under different conditions is less than 12 seconds. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Long short-term memory

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Data-Based Online Optimal Control for Multi-player Nonlinear Non-zero-Sum Games Using Recursive Least Squares

Data-Based Online Optimal Control for Multi-player Nonlinear...

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2021 China Automation Congress, CAC 2021

作者： Yang, Gaofu Song, Ruizhuo Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426473

In this paper, optimal control of nonlinear systems for non-zero-sum games is solved with a data-based and recursive least square. The new adjustment law is similar to experience replay algorithm which refer history data and the covariance matrix is introduced for storing historical data, which can avoid the waste of space and time caused by storing a large amount of historical data and collecting data. In tuning process, we use a discount factor which shows how trust to the collected data to guide adjustment law to update the weight. Meanwhile, discount factor can avoid the covariance matrix tending to zero due to accumulation of data. After that, the convergence of the weight is analyzed. Finally, using a simulation to verify the effectiveness of the tuning law. © 2021 IEEE

关键词： Covariance matrix

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Adaptive Neural Network Asymptotic Tracking Control for Autonomous Surface Vehicles

Adaptive Neural Network Asymptotic Tracking Control for Auto...

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Industrial Cyber-Physical systems (ICPS)

作者： Yongchao Liu Qingzhi Wang Baozeng Fu Institute of Complexity Science School of Automation Qingdao University Qingdao China Shandong Key Laboratory of Industrial Control Technology Qingdao China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

In this paper, an adaptive neural network asymptotic tracking control method is presented for autonomous surface vehicles (ASV) with unknown uncertainties. In the control design, a smooth function is integrated into backstepping construction, which can achieve asymptotic convergence. The neural networks are borrowed to approximate the lumped nonlinear functions encompassing the unknown dynamics. It can be proved that the tracking errors of ASV can asymptotically converge to zero and all signals of the ASV closed-loop system are bounded. We offer simulation images to exhibit the validity of the devised asymptotic control method of ASV.

关键词： Adaptation models Backstepping Uncertainty Adaptive systems Control design Process control Artificial neural networks

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"All-or-None" Dynamics and Local-Range Dominated Interaction Leading to Self-Organized Criticality in Neural System

SSRN

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SSRN 2023年

作者： Yang, Jinhao Ding, Yiming Di, Zengru Wang, Da-Hui School of Systems Science Beijing Normal University Beijing100875 China College of Science Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of System Science in Metallurgical Process Wuhan430065 China School of Systems Science Beijing Normal University Beijing100875 China International Academic Center of Complex Systems Beijing Normal University Zhuhai519087 China

Since the first observation of criticality in neural systems, there has been a consensus that the nervous system can operate in a critical state, and an increasing number of self-organized models equipped with various mechanisms have been proposed. However, we think that there are simple mechanisms underlying the criticality of neural systems. We, therefore, construct a neural network model to reveal the mechanism underlying criticality in neural systems. We found that a neural system consisting of neurons with "all-or-none" dynamics and local-range dominated interaction will exhibit critical behavior when properly driven. The "all-or-none" dynamics of single neuron and local-range dominated interaction are exactly the same mechanism of criticality in the BTW sandpile model, so we conclude that whatever mechanism causes the neural system to evolve to the state where short-range dominated interaction and appropriate input is received, critical behavior can be observed. © 2023, The Authors. All rights reserved.

关键词： Dynamics

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Model Reconstruction Based on Physical-Informed Polynomial Neural ODEs

Model Reconstruction Based on Physical-Informed Polynomial N...

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Data Driven Control and Learning systems (DDCLS)

作者： Zhang Chen Wei Zhu Jingsui Li Hanlin Bian Chao Pei School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing P. R. China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Neural networks are capable function approximators for data, but their lack of interpretability poses challenges. Physical-informed Polynomial Neural Ordinary Differential Equations (PIPNODEs) are proposed. They combine the constraints of prior knowledge of the data with interpretable Polynomial Neural Ordinary Differential Equations (PolyNODEs) to discover or approximate the governing equations. In this work, Neural Ordinary Differential Equations (NODEs) are categorized into two layers: a physical-informed term, which represents the priori knowledge of the data, and a discrepancy term, which is derived from the approximation of PolyNODEs. Pruning strategies are also used to remove redundant terms with coefficients lower than a certain threshold. We demonstrate the effectiveness and flexibility of this framework in a series of numerical algorithms with varying levels of prior knowledge. We found that having correct but incomplete physical information accelerates training and approaching thresholds compared to having incorrect physical information.

关键词： Training Accuracy Heuristic algorithms Ordinary differential equations Approximation algorithms Mathematical models Data models

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