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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Nikola N. Nikolov Aziz Hayitov Husen Sharifov 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 Bukhara Institute of Natural Resource Management of the National Research University «Tashkent Institute of Irrigation and Agricultural Mechanization institute» Tashkent Uzbekistan

The article gives the basic concepts of reliability, performance, durability, considers the issues of changing the technical state of the machine during operation. The models under consideration have the ability to introduce various perturbations in order to simulate physical defects, and numerical simulation on a computer made it possible to obtain solutions in the form of temporary realizations of oscillations for different states of the simulation object. The cooperative use of the full-scale method and mathematical modeling made it possible to reduce the volume of full-scale experiments and apply statistical methods of analysis in the problem of classifying the technical condition by constructing mathematical models of the probability of failure and uptime during their operating time. The content of the main types of machine states is revealed, considerable attention is paid to the issues of identifying and influencing failures and the causes of failures in the machine, the reasons for the loss of performance during operation.

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Power Loss Analysis of Energy Management System with Model Predictive control in Mae Hong Son Microgrid

Power Loss Analysis of Energy Management System with Model P...

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IEEE International Conference on Power Electronics, Intelligent control and Energy Systems (ICPEICES)

作者： Nattakit Prapanwattana Donlapat Dechawatanapaisal David Banjerdpongchai Abhishek Rajan Dept. of Electrical Engineering Faculty of Engineering Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Bangkok Thailand Dept. of Electrical Engineering National Institute of Technology Sikkim South Sikkim India

ISBN: (数字)9798350387193

ISBN: (纸本)9798350387209

Energy management system (EMS) is an important tool for energy efficiency and reliability of the power system. The optimal power dispatch of energy resources can be obtained using the nonlinear model predictive control (NMPC). It is formulated as an optimization problem subject to linear and nonlinear constraints. Although the existing system works well under the current conditions, power loss has not been considered. Power loss in transmission lines occurs due to their resistance and a high amount of power flow to loads connecting to the system. The power loss leads to decreased efficiency in the electrical system and reduces the lifespan of equipment because of the high temperature from loss. This paper aims to analyze the power loss in the Mae Hong Son (MHS) microgrid. To achieve the research objectives, we employ the EMS of MHS with NMPC and calculate power loss in transmission lines for a period of 7 days. EMS considers three objective functions, namely, total operating cost, total carbon dioxide emission, and combined economic and emission dispatch and take into account of three seasons consisting of rainy, winter, and summer.

关键词： Resistance Power transmission lines Microgrids Propagation losses Power system reliability Reliability Energy management systems Power generation Load flow Predictive control

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Dual-Channel Wind Power Forecasting Model Using Squeeze and Excitation Network

Dual-Channel Wind Power Forecasting Model Using Squeeze and ...

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Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Haonan Li Bozhen Jiang Zhengyang Ma Hua Geng Yi Liu Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China Department of Automation Tsinghua University Beijing China

Accurate wind power forecasting plays an increasingly important role in the field of wind power forecasting but still intractable in practice. In order to improve the accuracy of wind power forecasting, a novel model based on squeeze and excitation network (SENet) embedded in a dual-channel is proposed. The dual-channel mechanism integrates convolutional neural network and gated recurrent unit, both of which can be used without interfering with each other. SENet can increase the attention of each important features, thus improving the network efficiency. Compared with a single model, the proposed model has better feature extraction performance with the root mean square error of 29.9. The test results of wind power data based on Kaggle platform show that the proposed method outperforms several deep learning forecasting methods.

关键词： Neural networks Wind power generation Predictive models Logic gates Feature extraction Internet Convolutional neural networks

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Analysis of Operational Data and Self-learning control Rules for Mining Mill Equipment

Analysis of Operational Data and Self-learning Control Rules...

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Asian control Conference

作者： Guicheng Wang Liang Yuan Zhicheng Bai Guoliang Cai Ning Hua Xiaobin Li School of Electrical and Electronics Engineering Shanghai Institute of Technology Shanghai China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China Zijin Intelligent Control (Xiamen) Technology Co. Ltd. Xiamen China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The engineering application under industrial big-data analysis is of great significance for improving the optimization effect of enterprise production process control processes. By analyzing the operating principle of the semi-automatic mill and studying its control optimization strategy, based on the operational data of the SAG mill, industrial big-data analysis is adopted to self-learning its control optimization rules. Firstly, SPSS is used to preprocess the high-dimensional process data generated during the operation of the semi-automatic mill. Four parameters, namely power, axial pressure, grinding sound, and grinding concentration, are preliminarily selected. Then, PCA is used to screen and reduce the dimensionality of multidimensional data, and K-Means clustering algorithm is used to classify and identify the reduced dataset. After simulation research, the results show that PCA can reduce the redundancy of SAG mill operation data, and the control optimization rules formed by self-learning can serve as operational guidance for improving the efficiency and energy-saving of SAG mill operation. The effectiveness can be further verified in practical engineering applications in the later stage.

关键词： Dimensionality reduction Energy consumption Technological innovation Redundancy Force process control Clustering algorithms

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Supervised Dynamic Latent Variable Models for Fault Identification in Dynamic processes

Supervised Dynamic Latent Variable Models for Fault Identifi...

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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical processes, SAFEprocess 2021

作者： Niu, Qiqi Shen, Chengkai Lyu, Yuting Liu, Yi Zhou, Le Zhejiang University of Science Technology School of Automation and Electrical Engineering Zhejiang Hangzhou China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Zhejiang Hangzhou China

ISBN: (纸本)9781665401159

With an increasing application of the multivariate statistical process monitoring method, the fault identification becomes more and more crucial after the fault detection, which is benefited to fault troubleshooting effectively and quickly. To deal with the dynamic process and the impact of random noise on fault identification, a novel fault identification method based on supervised autoregressive dynamic latent variable is proposed in this paper. After the fault label structure is added on the unsupervised model, the relationship between fault information and dynamic latent feature is strengthened. Then, the fault cause is determined based on the fault relevance method. Finally, the validity of method is verified by a numerical example and an actual wastewater treatment case. © 2021 IEEE.

关键词： Fault detection

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A Koopman Operator-Based Finite Impulse Response Filter for Nonlinear Systems

A Koopman Operator-Based Finite Impulse Response Filter for ...

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IEEE Conference on Decision and control

作者： Zhichao Pan Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China department of chemical and materials engineering University of Alberta Edmonton Alberta Canada

This paper proposes a novel Koopman operator-based finite impulse response (KFIR) filter for nonlinear dynamic systems. This filter is generalized from the minimum variance unbiased (MVU) FIR filter for linear systems by using a global linear approximation of the nonlinear dynamics obtained from Koopman operator theory and the extended dynamic mode decomposition (EDMD) algorithm. Based on the recursive linear model, a reduced-order FIR filtering structure is proposed, and the optimal gain is derived to minimize the trace of the estimation error covariance. Unlike traditional methods, the KFIR filter requires no prior knowledge of the initial state and fully utilizes the data of a moving horizon. Simulation results show that the proposed filter has excellent robustness against unexpected modeling uncertainties and inaccurate noise information, making it suitable for real applications.

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Interval Observers Design for Discrete-Time Linear Systems with Uncertainties 1st

Interval Observers Design for Discrete-Time Linear Systems w...

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1st International Conference on Applied Intelligence, ICAI 2023

作者： Zhirabok, Alexey Zuev, Alexander Filaretov, Vladimir Yuan, Changan Far Eastern Federal University Vladivostok690992 Russia Institute of Marine Technology Problems Vladivostok690950 Russia Institute of Automation and Process Control Vladivostok690950 Russia Vladivostok State University Vladivostok690014 Russia Guangxi Academy of Science Nanning530007 China

ISBN: (纸本)9789819708260

The paper studies the problem of designing interval observers for discrete-time linear dynamic systems under the external disturbances, measurement noises, and unknown system parameters. To construct such observers, we use not the original system but its reduced-order model of the original system of minimal dimension which is insensitive to the disturbances. The observers are designed in such a way to estimate the prescribed linear function of the original system state vector. Canonical form of the observer is used that allows to simplify the design procedure. The obtained results are displayed by example of the electric servoactuator. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Linear control systems

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On Assignments Verification during the ICS Databases Lifecycle 14

On Assignments Verification during the ICS Databases Lifecyc...

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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Budynkova, Elizaveta Baybulatov, Artur Joint Stock Company «aLFA-BANK» Business Process Automation Directorate Moscow Russia Ivery Prangishvili Laboratory 31 'Distributed Data-Analysis and Control Systems' V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia

ISBN: (纸本)9781665412308

Today, Industrial control System (ICS) databases are incredibly complicated with quite prolonged iterative lifecycle where every new iteration is driven by a new version of the database assignment. For the correct databases development, the assignments should be consistent and correspond to special requirements, but this is not always the case. Therefore, the checking, or verification, of the assignments is becoming especially important. However, the appropriate problem of databases assignments verification is not widely discussed, and available verification methods are not suitable enough for solving the problem. The article clarifies the place of the assignments verification in the ICS databases lifecycle and presents a novel algorithm for the assignments verification. The particular implementation of the algorithm is also considered. As an example, the results of the verification of the assignments for the NPP ICS databases are presented. © 2021 IEEE.

关键词： Database systems

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Adaptive Energy Management Strategy to Avoid Battery Temperature Peaks in Fuel Cell Electric Trucks

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IFAC-PapersOnLine 2022年第24期55卷 311-316页

作者： Alessandro Ferrara Matthias Hütter Christoph Hametner Institute of Mechanics and Mechatronics Division of Process Control and Automation TU Wien Vienna Austria AVL List GmbH Graz Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

Thermal management is essential in electric vehicles to preserve battery life. In particular, avoiding temperature peaks is critical to prevent accelerated degradation. The battery thermal management problem is crucial in fuel cell electric trucks due to the heavy vehicle weight, especially on mountain or hilly roads. Therefore, this paper proposes an energy management strategy that reduces battery degradation by limiting its usage at high temperatures to allow its cooldown and avoid peaks. The energy management strategy is adaptive because the main control parameters for the fuel cell/battery power-split are adjusted depending on the battery temperature. The comparison between adaptive and non-adaptive strategies proves the effectiveness of the proposed formulation in avoiding temperature peaks without hindering fuel consumption or fuel cell degradation. The robustness of the proposed energy management strategy is validated with simulations of several real-world driving cycles with various speed and elevation profiles.

关键词： Energy Management Heavy-Duty Fuel Cell Vehicle Adaptive control Battery Temperature Fuel Cell Degradation Battery Thermal Management

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A parallel intelligent system for optimizing high-speed railway rescheduling by learning 1

A parallel intelligent system for optimizing high-speed rail...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Yang, Pengxin Cui, Dongliang Dai, Xuewu Lv, Yisheng Dong, Hairong Wang, Xinghao Liu, Ruiguang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China

ISBN: (纸本)9781665433372

The railway system is a complex system because of many constraints, randomness and high security requirements, so it is difficult to establish an accurate mathematical model for it, which brings great challenges to railway scheduling. Parallel intelligence theory can effectively solve the modeling, analysis and control of complex systems, so it has a wide range of applications in the field of intelligent transportation. In this paper, we build an artificial system according to the actual system, and use the surrogate modelling to carry out the calculation experiments, and proposed a parallel scheduling system based on the parallel intelligence method. Select a case to design scenario and perform computational experiment, the scheduling strategy is given and the scheduling strategy is analyzed. © 2021 IEEE.

关键词： Intelligent systems

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