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60th IEEE/IAS Industrial and Commercial Power systems Technical Conference, I and CPS 2024

作者： Sun, Feiyu Cai, Dongsheng Zhang, Zhenyuan Huang, Qi University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering Chengdu611731 China Chengdu University of Technology College of Nuclear Technology and Automation Engineering 610059 China Southwest University of Science and Technology School of Information Engineering Sichuan Mianyang China

ISBN: (纸本)9798350345308

Wind and solar energy inverter-based resources (IBRs) has been employed extensively with the aim of carbon neutrality. Power systems also make extensive use of power electronic converters, leading to interactions between IBRs and with the grid, causing high frequency oscillation (HFO) problems. It damages equipment and jeopardizes the security of the system. To identify HFO components above 100 Hz, this research use Phasor measurement Unit (PMU) instantaneous value data to determine the HFO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the HFO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple HFO modes. The simulation results show that the proposed method has high identification bandwidth, accuracy and strong flexibility. © 2024 IEEE.

关键词： Discrete Fourier transforms

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Constraint-Following Based Adaptive Robust control for Underactuated Mechanical systems

Constraint-Following Based Adaptive Robust Control for Under...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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Sensorless control of SPMSM Based on Generalized Super-Twisting Observer and Non-Smooth controller

Sensorless Control of SPMSM Based on Generalized Super-Twist...

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Chinese control Conference (CCC)

作者： Dejin Chen Ke Yu Shihong Ding Xiangyu Wang Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Electrical and Information Engineering Zhenjiang China

To enhance the estimation accuracy and dynamic performance of sensorless surface-mounted permanent magnet synchronous motor (SPMSM) drives, a sensorless control scheme based on generalized super-twisting observer (GSTO) and non-smooth controller is proposed. Firstly, a GSTO for back electromotive force (back-EMF) estimation is proposed. Compared with the conventional super-twisting observer, the GSTO has a faster convergence rate and stronger robustness due to the additional terms. Then a linear extended state observer (LESO) is adopted to estimate the position, speed, and lumped disturbance at the same time. Moreover, a non-smooth composite speed controller is designed by combining the disturbance feed-forward compensation. Compared with the conventional PI speed controller, the non-smooth controller has a shorter settling time and a better disturbance rejection ability. Finally, the effectiveness of the proposed method is verified by simulation results.

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A High-Quality View Synthesis System for Sparse Rgb-D Input

SSRN

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SSRN 2024年

作者： Zhao, Ziyu Lu, Xiaobo Zhou, Sifan Chiang, Patrick Y.I.N. School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Key Laboratory of ASIC and System Fudan University Shanghai China

Recent research in neural rendering has achieved impressive results in the field of novel view synthesis. However, high-quality view synthesis with sparse source views remains a challenging task, as the reduction in the number of source views significantly degrades the synthesis quality. In this paper, we present a novel view synthesis system that exploits RGB-D pairs from sparse source views. First, we introduce a two-branch feature extraction network to embed the geometric clues from depth maps into the texture information of color images and fuse it with regularized Fourier mapping features. Second, a distance-aware feature query method, which constructs multi-level feature maps, is proposed to ensure high-fidelity details across different distance views. Then, we apply an occupancy network to perform occupancy prediction on raw point cloud. By integrating occupancy probabilities and extracted features, we use a prediction network with geometric information as an additional input to obtain the color and density of sampled points, and synthesize the target view using neural volume rendering. To prevent model degradation and enhance efficiency, we design an efficient sampling strategy based on Gaussian Mixture Model. Moreover, we introduce pixel-wise local regularization and full-image global geometric regularization to optimize the model. Extensive experiments show that the proposed method can achieve the state-of-the-art results for novel view synthesis with sparse inputs, and the model performance has been significantly improved in different scenarios. © 2024, The Authors. All rights reserved.

关键词： Geometry

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Research on Seismic Bracing Monitoring System Based on Wireless Transmission

Research on Seismic Bracing Monitoring System Based on Wirel...

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IEEE International Conference on Mechatronics and automation

作者： Lujia Wang Baofeng Zhang Wei Wang Zhiwei Li Junchao Zhu Tianjin Key Laboratory of Control Theory & Application of Complex Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

Real-time data acquisition and monitoring of seismic bracings can help to maintain their effectiveness during service life and to improve the seismic resistance and disaster mitigation effects when strong earthquakes occur. In order to monitor real-time states of the seismic bracing, an intelligent monitoring system based on wireless transmission technology was designed. The system used CC2530 Zigbee module to establish a ZigBee wireless LAN, and combined MEMS vibration sensors and strain gauges. Meanwhile, the system used ESP32 to upload the measurement data to OneNET cloud platform through MQTT wireless communication protocol. The function of data visualization was designed so as to realize real-time monitoring of seismic bracing states. The experimental results showed that the proposed wireless monitoring system can reliably execute real-time data collection, storage, display, and hazard warning to guarantee the effectiveness of seismic bracings.

关键词： Wireless communication Vibrations Wireless sensor networks Wireless LAN Disasters Data visualization Zigbee

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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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Enhancing sensitivity of ultrasmall rotation velocity measurements with biased quantum weak measurement 41

Enhancing sensitivity of ultrasmall rotation velocity measur...

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第41届中国控制会议

作者： Guang-Jun Wang Xue-Ying Duan Jing-Hui Huang Xiang-Yun Hu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Institute of Geophysics and Geomatics China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Recently,biased quantum weak measurement has shown higher precision than both conventional measurement and standard quantum weak measurement in optical *** this work,a scheme of detecting the ultrasmall rotation velocity in Sagnac's interferometer with biased quantum weak measurement is *** biased quantum weak measurement,additional progress of pre-coupling is introduced in standard quantum weak measurement to enhance the sensitivity for the estimated parameter,and the cost of the reduction of photons in the post-selection by pre-coupling may not impact the measurement because eliminating the saturation effect of the detector *** addition,our numerical results show that the scheme with biased quantum weak measurement can obtain a higher sensitivity for rotation velocity measurement than the scheme with standard quantum weak measurement.

关键词： quantum measurement quantum weak measurement quantum optical rotation velocity sensitivity enhanced

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A Segmented Sliding Window-Based Comprehensive Periodic Feature Extraction Method for APT Classification

A Segmented Sliding Window-Based Comprehensive Periodic Feat...

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International Conference on control and automation (ICCA)

作者： Wei Song Tiejun Wu Ya Zhang School of Software Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Cyber Science and Engineering Southeast University. School of Automation Southeast University Nanjing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper studies the classification problem of Advanced Persistent Threat (APT) attacks and proposes a comprehensive periodic feature extraction method based on sliding window division. A new data processing approach is proposed. Considering the characteristics of APT attacks, the life cycle of APT traffic data is divided into three stages. The traffic data from each stage is sampled in a piecewise manner and divided into separate training and testing sets, and then the training and testing subsets are merged. For the integrated sets, a sliding window-based partition approach is employed to obtain training and testing window samples, while extracting features from each individual sample. Then, this paper proposes a differential-based periodic feature extraction methodology to capture the dynamic information present in APT traffic and integrate it with fundamental static features, thereby forming effective comprehensive features. After combining these static and differential features, a comprehensive foundation is established for model training. Finally, the effectiveness of the algorithm is verified using decision tree model, and its superiority is demonstrated by comparing it with traditional partition methods based on data streams.

关键词： Training Heuristic algorithms Feature extraction Data models Partitioning algorithms Classification algorithms Decision trees

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Data-Driven Distributed Robust Consensus Kalman Filtering for Sensor Networks

Data-Driven Distributed Robust Consensus Kalman Filtering fo...

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2021 China automation Congress, CAC 2021

作者： Zhou, Ziai Wu, Hao Zhang, Ya School of Automation Southeast University Nanjing China 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China 210096

ISBN: (纸本)9781665426473

This paper mainly studies the distributed robust filtering problem for wireless sensor networks without knowing the variance of the driving noise and measuring noise. A distributed filtering algorithm based on leader-follower consensus strategy is developed. Firstly, from limited sampling data of noises, the empirical distribution of the noises which play a critical role in filtering is given. Secondly, by formulating the problem as a zero-sum game problem and using dynamic programming approach, an optimal distributed robust filtering policy with Wasserstein penalty for the leader is obtained. Then, by using an adaptively weighting average consensus protocol, the filtering algorithm for followers is given. The effectiveness of the proposed filter is demonstrated through simulations. © 2021 IEEE

关键词： Dynamic programming

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Double wavelet threshold filter design for real-time adaptive denoising in OA-ICOS

Double wavelet threshold filter design for real-time adaptiv...

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Jiangsu Annual Conference on automation (JACA 2024)

作者： Yixin Deng Zairan Wang Yang-Yang Chen Qin Liu Xiangyu Wang School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing People's Republic of China School of Cyber Science and Engineering Southeast University Nanjing People's Republic of China

ISBN: (数字)9781837242719

In the Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) technique, single-stage filters are commonly used to reduce noise and improve the signal-to-noise ratio, enabling more precise CO2 concentration detection. However, these filters often underperform under real-time conditions. To enhance real-time performance, this paper proposes a novel framework based on Double Wavelet Threshold Filter (DWTF) that adaptively suppresses noise while preserving key features of CO2 concentration signal. Firstly, one wavelet threshold filter (WT) is introduced to calculate the mean of the current sequence, providing an initial denoising step. Secondly, another WT is employed to extract features from a longer sequence for adaptive computation of the discount factor. Finally, an exponential moving average filter (EMA) is applied to combine both current and historical data to produce a smoother aggregated output. To validate the effectiveness, DWTF was compared with other conventional algorithms for a CO2 dataset with three distinct states: smooth, ship and mutant, obtained by OA-ICOS. The experimental results demonstrate that DWTF performs effectively in all three states.

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