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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Mirhalil A. Ismailov Nikola N. Nikolov Mariela Alexandrova Department "Automation and Control of Technology Process in Production" «Tashkent Institute of Irrigation and Agricultural Mechanization Engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

ISBN: (数字)9798350353907

ISBN: (纸本)9798350353914

The article discusses the theoretical foundations of the design of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. In accordance with the requirements of the methodology for selecting efficiency criteria, it is necessary to develop structural diagrams of measuring devices. For these purposes, the standard deviation of the random error is determined, characterizing the accuracy. It includes the main components: sensitivity error, zero error and additive component. Mathematical models of structures are constructed and the standard deviation of random errors, which are caused by certain parameters and additive fluctuations, is calculated. A single-parameter ultrahigh-frequency method for determining the moisture content is proposed. This method provides high accuracy of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. The measuring device can be used in the agricultural industry, where humidity is one of the important parameters, starting with harvesting and ending with the release of finished products.

关键词： Meters Additives Accuracy Sensitivity Moisture UHF measurements Mathematical models Frequency measurement Informatics Standards

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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Finite-Time Adaptive Quantized control of Switched Constrained Nonlinear Systems

Finite-Time Adaptive Quantized Control of Switched Constrain...

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IEEE International Conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Penghao Chen Xiaoli Luan Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

In this paper, the finite-time adaptive control issue is addressed for a class of switched strict-feedback nonlinear systems with input quantization and output constraints. Firstly, the barrier Lyapunov function is introduced to cope with statistic output constraints, and with the help of Young's inequality, only one learning parameter of neural networks needs to be tuned online at each step of recursion. Then, a hysteresis quantizer is introduced to handle the input signal. Finally, by appropriately choosing the initial value of the switched subsystem and using the characteristics of dynamic surface control, finite-time adaptive neural quantized control is designed to guarantee that all signals are semi-globally practical finite-time stable. Simulation results verify the effectiveness of the proposed means.

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The Specifics of the Organization of Independent Work of Students in the System of Secondary Vocational Education In Uzbekistan in the Context of the Transition to a Digital Economy 3

The Specifics of the Organization of Independent Work of Stu...

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3rd International Conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Ubaydullayeva, Shakhnoza Tadjiyeva, Gavhar Ubaydullayeva, Dilorom Kadirova, Nilufar Gulyamova, Zarina Subanova, Dilafruz National Research University «tashkent Institute of Irrigation and Agricultural Mechanization Engineers» Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan University Named after Nizami Department of Theory and Methodology of Teaching English Language Tashkent State Pedagogical Tashkent Uzbekistan

ISBN: (纸本)9798350326567

The problem of self-education of students of professional colleges is one of the most important in Uzbekistan. With the improvement of the education system, the processes of education and upbringing, new aspects of this problem appear, associated with changing the content and setting new tasks. Social transformations caused by the transition to the information society actualize the problem of the formation of a new paradigm of education, which is characterized by a redistribution of emphasis from educational activities to self-educational ones. The use of electronic educational resources (computer educational and methodological complexes, textbooks, teaching aids, virtual laboratories, stands, posters, etc.) is today one of the conditions for increasing the effectiveness of training - the psychological, theoretical and practical readiness of students of professional colleges for independent work. Uzbekistan's transition to a market economy dictates new requirements for a specialist, one of the main qualities of which is independence. The formation of this quality is determined, among other things, by the organization of independent work as a type of educational activity in educational institutions of secondary vocational education, which have their own specifics and features © 2023 IEEE.

关键词： Students

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Experience Replay Q(λ)-learning with Leader-Following control for Multi-Evader Pursuit Evasion Games 5

Experience Replay Q(λ)-learning with Leader-Following Contr...

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5th IEEE Information Technology, Networking, Electronic and automation control Conference, ITNEC 2021

作者： Zhu, Zhe-Yang Liu, Cheng-Lin Jiangnan University Key Laboratory of Advanced Process Control for Light Industry Institute of Automation Wuxi214122 China

ISBN: (纸本)9781665415989

This paper addresses a pursuit evasion game with multi-evader, and only some pursuers which are termed as leading pursuers can access the positions of the evaders during the pursuit. Furthermore, Q(λ)-learning is utilized to train the pursuers. Because Q(λ)-learning exhibits slow convergence, a new method that combines experience replay Q(λ)-learning and dynamic target assignment is introduced. Simulation shows that the proposed method achieves better convergence results than Q(λ)-learning in our multi-evader pursuit evasion game. © 2021 IEEE.

关键词： Reinforcement learning

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Time-Attention Graph Convolutional Network Soft Sensor in Biochemical processes 4

Time-Attention Graph Convolutional Network Soft Sensor in Bi...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Most data-driven soft sensor methods can model nonlinear time-varying characteristics of biochemical processes. However, the intrinsic relationship between variables, which is helpful for understanding model behavior, has rarely been investigated in existing data-driven methods. In this work, a novel soft sensor model of time-attention graph convolutional network (TA-GCN) is proposed, which jointly leverages variable relationships and long-term temporal dependencies to improve interpretability and prediction accuracy. This model first uses the maximum information coefficient to construct a topology graph and trains edge strengths end-to-end. The data are then encoded in the spatial-temporal dimension based on GCN and attention mechanism. Finally, the empirical knowledge that analyzes the operating state of the process and graph are combined to explain the model behavior. In comparison to existing soft sensors, TA-GCN enables efficient and scalable training for long-term spatial-temporal dependencies. Experimental results on InPenSim dataset demonstrate that TA-GCN is competitive with state-of-the-art methods. © 2022 IEEE.

关键词： Convolution

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Topology-Informed Graph Convolutional Network for Fault Diagnosis 11

Topology-Informed Graph Convolutional Network for Fault Diag...

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Jia, Mingwei Liu, Yi Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

The development of an accurate data-driven fault diagnosis model faces several obstacles. One significant challenge is how to combine the model with the process mechanism rationally and improve the model interpretability. In this work, a fault diagnosis method based on a topology-informed graph convolutional network (TIGCN) is proposed. This model first uses the empirical knowledge that analyzes the operating state of the process and combines the operating data to construct a signed directed graph. Then the operating data is divided into three modalities in the time dimension. The model utilizes a well-designed spatial-temporal convolutional layer and signed directed graph to construct different modalities separately to effectively detect fault types. The superior fault diagnosis performance of the proposed TIGCN model is demonstrated on the Tennessee-Eastman process as compared to traditional approaches. © 2022 IEEE.

关键词： Failure analysis

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Transductive Transfer Broad Learning Soft Sensor for Multimode Quality Prediction

Transductive Transfer Broad Learning Soft Sensor for Multimo...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Jialiang Zhu Hongying Deng Danya Xu Tao Yang Yi Liu Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

In chemical processes, reliable soft sensors are generally established by enough labeled data. However, in most multimode processes, the collection of sufficient labeled data is difficult due to the high cost and complexity. In this work, transductive transfer broad learning (TTBL) is proposed for multimode quality prediction. By transferring the useful information from the related domain, unlabeled data in the prediction domain is utilized for modeling. First, the data feature is extracted by the feature and enhancement nodes. The similarity information of current and related domain data is captured by the $k$ nearest-neighbor graph. Then, label information in the related domain can be transferred and similar information in the same domain can be retained by the manifold regularization framework. Finally, the output weight can be effectively calculated by the ridge regression algorithm. Experimental results on continuous stirred tank reactor datasets show the superiority of TTBL, compared with several common methods.

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Synthesis of Interval Observers for Discrete-Time Linear Systems with Parametric Uncertainties

SSRN

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SSRN 2023年

作者： Zhirabok, Alexey Zuev, Alexander Filaretov, Vladinir Far Eastern Federal University Vladivostok Russia Institute of Marine Technology Problems Vladivostok Russia Institute of Automation and Process Control Vladivostok Russia

The paper considers the problem to construct interval observers for discretetime linear systems under the external disturbances, measurement noises, and unknown parameters. To construct such observers, we use not the original system but its reduced-order model of minimal dimension which does not depend on the disturbances or has minimal sensitivity to them. The observers are designed in such a way to estimate the prescribed function of the original system vector of state. The obtained results are displayed by example of the electric servoactuator. © 2023, The Authors. All rights reserved.

关键词： Linear systems

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Nonlinear Quasi-unknown Input Observer Design using Dissipativity 63

Nonlinear Quasi-unknown Input Observer Design using Dissipat...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Schaum, A. Koch, S. Moreno, J.A. University of Hohenheim Chair of Process Analytics The Computational Science Hub Stuttgart Germany Institute of Automation and Control Graz University of Technology Graz Austria Instituto de Ingeniería Universidad Nacional Autónoma de México Coordinación de Eléetrica y Computación Ciudad de México Mexico

ISBN: (纸本)9798350316339

This paper addresses the design of nonlinear quasi-unknown input observers for systems that can be interpreted as an interconnection of a linear dynamical subsystem with a static nonlinear feedback subject to additive perturbations. As assumed classically an exosystem is considered describing the dynamics of the perturbation, meaning that the dynamical mechanisms giving rise to the perturbation are sufficiently well known but the underlying initial condition is unknown. Extending classical results based on the Sylvester equation, and combining them with well-established dissipativity concepts and design methods, a new approach for quasi-unknown input observer design is obtained. It simplifies previous work on general unknown input observer design by exploiting the structural knowledge about the exosystem, without extending the state dimension. The approach is illustrated with numerical case examples. © 2024 IEEE.

关键词： Nonlinear simulations

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