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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry.

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Multiple Anti-windup Loops under Multiple Activations:Dynamic Case to Enlarge Domain of Attraction

Multiple Anti-windup Loops under Multiple Activations:Dynami...

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第三十二届中国控制会议

作者： Xiongjun Wu Ziyang Meng The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China ACCESS Linnaeus Centre School of Electrical EngineeringRoyal Institute of Technology

ISBN: (纸本)9781479900305

A multiple anti-windup loops under multiple dynamic activations strategy is proposed to enlarge the domain of attraction. This work is parallel to the multiple activation case with static *** traditional anti-windup compensator is activated immediately as the saturation *** was shown recently that,by delaying the activation of the anti-windup mechanism to a certain level,the performance can be improved for the closed-loop *** was further shown that better performance can be obtained by activating an anti-windup mechanism in anticipation of actuator saturation,in comparison with the delayed activation *** paper considers the anti-windup design problem of enlarging domain of attraction under a dynamic multiple activation *** this multiple activation scheme,the anticipatory,delayed and immediate activation mechanism is incorporated in the same framework simultaneously.A furthermore significant performance improvements over both the immediate and delayed activation schemes can be *** proposed dynamic multiple activation scheme established a unified anti-windup framework and can be readily extended to the traditional immediate,delayed and anticipatory activation anti-windup mechanisms.

关键词： Anti-windup dynamic compensator domain of attraction multiple activations

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Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs

arXiv

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arXiv 2019年

作者： Liu, Zihan Meng, Lubin Zhang, Xiao Fang, Weili Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Design and Environment National University of Singapore 117566 Singapore Zhejiang Lab Hangzhou311121 China

Multiple convolutional neural network (CNN) classifiers have been proposed for electroencephalogram (EEG) based brain-computer interfaces (BCIs). However, CNN models have been found vulnerable to universal adversarial perturbations (UAPs), which are small and example-independent, yet powerful enough to degrade the performance of a CNN model, when added to a benign example. This paper proposes a novel total loss minimization (TLM) approach to generate UAPs for EEG-based BCIs. Experimental results demonstrated the effectiveness of TLM on three popular CNN classifiers for both target and non-target attacks. We also verified the transferability of UAPs in EEG-based BCI systems. To our knowledge, this is the first study on UAPs of CNN classifiers in EEG-based BCIs. UAPs are easy to construct, and can attack BCIs in real-time, exposing a potentially critical security concern of BCIs. Copyright © 2019, The Authors. All rights reserved.

关键词： Electroencephalography

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Robust Disturbance-Rejection for a Class of Nonlinear Systems

Robust Disturbance-Rejection for a Class of Nonlinear System...

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第37届中国控制会议

作者： Pan Yu Kang-Zhi Liu Min Wu Jinhua She Department of Electrical and Electronic Engineering Chiba University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Information Science and Engineering Central South University School of Automation China University of Geosciences School of Engineering Tokyo University of Technology

This paper presents a robust disturbance-rejection method for a system with a time-variant nonlinearity and a disturbance. The nonlinear dynamics which satisfies Lipschitz condition is unknown. The disturbance is also unknown but *** advantage of stable inversion, an improved EID(IEID) is utilized to deal with the total effect of the nonlinearity and disturbance. To reduce the conservativeness of system design, a feedback control gain is obtained in prior to the control gains of the observer and the IEID estimator. Then a Lyapunov functional considering the information of the nonlinearity is constructed and based on that, a linear-matrix-inequality(LMI)-based stability condition is derived to acquire the gains of the observer and the IEID estimator. Two tuning parameters are introduced in the LMI to enable the adjustment of disturbance-rejection performance. Finally, simulations for a flight control system show that the developed method has good robustness. Comparisons with disturbance-observer-based control(DOBC), composite DOBC and H control, and conventional EID-based control methods demonstrate the effectiveness of the developed method and its advantages over others.

关键词： Disturbance-rejection improved equivalent-input-disturbance（EID） linear matrix inequality（LMI） nonlinear system robustness

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Dielectric Spectrum of Random Copolymerization Polypropylene Nanocomposites Doped with Nano Silica at Different Temperatures

Dielectric Spectrum of Random Copolymerization Polypropylene...

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International Conference on High Voltage Engineering and Application, ICHVE

作者： Rujia Men Zhipeng Lei Jiancheng Song Kunying Han Lu Li Chuangyang Li Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT USA

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Random copolymerization polypropylene (PPR), a recyclable thermoplastic material with a melting temperature of over 150°C and excellent mechanical properties, has potential to become the insulation materials used in high voltage cables. To investigate dielectric properties of PPR and its nanocomposites at different temperatures, especially the dielectric spectrum at high temperatures, film samples of PPR and its nanocomposites doped with different content of nano silica were prepared. The microscopic morphologies were observed firstly for analyzing the dispersion of nanoparticles. Then the dielectric spectrums were measured at temperatures of 30, 50, 70, 90, 110 and 130°C. After this, the effects of nanoparticle content, temperature and frequency on the relative permittivity and dielectric dissipation factors are discussed and the mechanism is analyzed. It can be concluded that relative permittivity of PPR and its nanocomposites are almost unaffected by temperature in the range of 30 - 110°C and remains relatively low values. When the temperature is below 110°C, the relative permittivity of the PPR nanocomposites increases with the increase of temperature; And when the temperature is 110°C or above, the value is related to the applied voltage frequency and the content of nanoparticles. And with the temperature rising, the dielectric dissipation factor of PPR nanocomposites have an evident increase at lower frequency, which contributes to the DC conductivity.

关键词： Temperature Nanocomposites Permittivity Dielectrics Temperature measurement Nanoparticles Time-frequency analysis

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Optimal Scaled Average Consensus control of Discrete-Time Multi-Agent Systems Based on Adaptive Dynamic Programming

Optimal Scaled Average Consensus Control of Discrete-Time Mu...

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Chinese control Conference (CCC)

作者： Peiyu Zhai Mengji Shi Weihao Li Jiangfeng Yue Kaiyu Qin Jinwei Bai Ruhao Hua School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China China Aerodynamics Research and Development Center Computational Aerodynamics Institute Mianyang China

This paper investigates the data-driven scaled average consensus control problem of discrete-time (DT) multi-agent systems. An optimal distributed control scheme is designed to solve this problem and enable model-free online training based on adaptive dynamic programming (ADP). Firstly, the optimal scaled average consensus problem is defined via Bellman optimality principle. Then, the ADP algorithm is designed to calculate a proper approximate solution for the discrete-time Hamilton-Jacobi-Bellman (DT-HJB) equation based on generalized policy iteration. In addition, critic-actor neural networks are well constructed to fit the iterative control law and performance indices to realize the model-free online training for the data-driven control. Finally, some simulation results are given to verify the validity of the proposed optimal distributed control scheme.

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Dielectric Strength of Ethylene Propylene Rubber under Thermal and Mechanical Stress

Dielectric Strength of Ethylene Propylene Rubber under Therm...

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International Conference on High Voltage Engineering and Application, ICHVE

作者： Yang Liu Rujia Men Muqin Tian Ye Wang Kunying Han Zhipeng Lei Chuangyang Li Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT USA

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

In order to find out the effect of temperature and mechanical stress on the dielectric breakdown strength of Ethylene Propylene Rubber (EPR), AC breakdown tests of EPR samples were carried out at different temperatures and compressive stress. Two-parameter Weibull statistical distribution was used to analyze the breakdown strength. The experimental results show that the dielectric strength of EPR decreases with the increase of temperature when only temperature is applied. Under the same temperature, the breakdown strength of EPR firstly increases with the compressive stress rising, gradually reaches a maximum and finally shows a decreasing tendency. It's due to the effect of compressive stress on the intermolecular distance and thermal expansion of EPR.

关键词： Electric breakdown Stress Compressive stress Insulation Dielectric breakdown Bars Electric fields

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Maintenance Optimization for Combined Heat and Power Unit Based on Opportunistic Maintenance Strategy

Maintenance Optimization for Combined Heat and Power Unit Ba...

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IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)

作者： Yumin Zhang Xingquan Ji Yixiao Yu Bo Xu Xueshan Han Lin Zhang College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Energy Research Institute Co. Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

Integrated energy system is composed of different multiple energy systems. When the combined heat and power (CHP) unit fails, more than one energy systems can be influenced. Therefore, it is very important to improve the reliability of CHP unit. In this paper, we propose a maintenance decision making model for CHP unit based on opportunistic maintenance strategy. Firstly, the expression of the availability of CHP unit considering opportunistic maintenance is derived. And then, in order to quantify the impact of different maintenance strategies on system operation, system operation risk is given taking electrical load loss and thermal load loss into account. Finally, maintenance decision making model of the CHP unit is established with maintenance constraints. Case studies show that the model can optimize maintenance strategies and improve the reliability of CHP unit and the overall system efficiency.

关键词： Maintenance engineering Cogeneration Reliability Power system reliability Resistance heating Couplings

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Anti-windup Design for Active Disturbance Rejection control

Anti-windup Design for Active Disturbance Rejection Control

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第三十三届中国控制会议

作者： Xiongjun Wu Jiaoni Pang Tao Yang The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China ACCESS Linnaeus Centre School of Electrical Engineering Royal Institute of Technology

ISBN: (纸本)9781479947249

An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection control(ADRC) mechanism, to deal with the input saturation nonlinearity and meanwhile reject the disturbance automatically by using Extended State Observer(ESO). The output of anti-windup compensator is treated as a part of unknown disturbances and is introduced into the ESO, which can online observe both internal and external disturbances(parameter uncertainties and model mismatches). The controller input is yielded by using a nonlinear feedback combination, and it is used to compensate the integrator windup caused by the saturation nonlinearity element. On the other hand, in order to determine the parameters of the ESO and the anti-windup compensator feedback gain, the L2 gain is adopted. The effectiveness and the robustness against model and parameter uncertainties of the proposed method is verified by an example of the seeker platform.

关键词： Actuator saturation,Anti-windup design,Active disturbance rejection,Extended State Observer(ESO),Tracking Differentiator

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Performance Analysis of Distributed Filtering under Mismatched Noise Covariances

arXiv

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arXiv 2024年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems, namely the standard performance evaluation index, the nominal performance evaluation index, and the estimation error covariance. We derive difference expressions among these indices and establish one-step relations among them under various mismatched noise covariance scenarios. We particularly reveal the effect of the consensus fusion on these relations. Furthermore, the recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these indices under the collective observability condition, and show this convergence condition of the nominal performance evaluation index can guarantee the convergence of the estimation error covariance. Additionally, we prove that the estimation error covariance of the consensus-based distributed filter under mismatched noise covariances can be bounded by the Frobenius norms of the noise covariance deviations and the trace of the nominal performance evaluation index. Finally, the effectiveness of the theoretical results is verified by numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Wiener filtering

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