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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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Real-time Hybrid System Identification with Online Deterministic Annealing

arXiv

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arXiv 2024年

作者： Mavridis, Christos N. Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

We introduce a real-time identification method for discrete-time state-dependent switching systems in both the input-output and state-space domains. In particular, we design a system of adaptive algorithms running in two timescales;a stochastic approximation algorithm implements an online deterministic annealing scheme at a slow timescale and estimates the mode-switching signal, and an recursive identification algorithm runs at a faster timescale and updates the parameters of the local models based on the estimate of the switching signal. We first focus on piece-wise affine systems and discuss identifiability conditions and convergence properties based on the theory of two-timescale stochastic approximation. In contrast to standard identification algorithms for switched systems, the proposed approach gradually estimates the number of modes and is appropriate for real-time system identification using sequential data acquisition. The progressive nature of the algorithm improves computational efficiency and provides real-time control over the performance-complexity trade-off. Finally, we address specific challenges that arise in the application of the proposed methodology in identification of more general switching systems. Simulation results validate the efficacy of the proposed methodology. © 2024, CC BY.

关键词： Stochastic systems

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Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications

arXiv

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arXiv 2024年

作者： Engelaar, Maico H.W. Zhang, Zengjie Vlahakis, Eleftherios E. Dimarogonas, Dimos V. Lazar, Mircea Haesaert, Sofie Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper addresses the control synthesis of heterogeneous stochastic linear multi-agent systems with real-time allocation of signal temporal logic (STL) specifications. Based on previous work, we decompose specifications into sub-specifications on the individual agent level. To leverage the efficiency of task allocation, a heuristic filter evaluates potential task allocation based on STL robustness, and subsequently, an auctioning algorithm determines the definitive allocation of specifications. Finally, a control strategy is synthesized for each agent-specification pair using tube-based model predictive control (MPC), ensuring provable probabilistic satisfaction. We demonstrate the efficacy of the proposed methods using a multi-shuttle scenario that highlights a promising extension to automated driving applications like vehicle routing. © 2024, CC BY-NC-ND.

关键词： Stochastic systems

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Design of Personalization Warehouse Management Platform Based on SaaS Model 25

Design of Personalization Warehouse Management Platform Base...

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25th IEEE International Conference on computer Supported Cooperative Work in Design, CSCWD 2022

作者： Guo, Qi Sun, Hongbo Ji, Wen Yantai University School of Computer and Control Engineering Shandong Yantai264005 China Institute of Computing Technology Chinese Academy of Science Beijing100190 China

ISBN: (纸本)9781665405270

SaaS is widely used in the fields of operation management, business process outsourcing, data analysis, and information security. However, with the improvement of the degree of information, the generalized SaaS platform is unable to satisfy the requirements of enterprise personalization. SaaS products face great challenges in personalized customization technology due to the application of multi-tenant architecture. The challenges include multi-tenant customization in SaaS model, data isolation during customization, and mapping of multi-tenant virtual warehouse locations to actual locations. Therefore, we decompose personalization technology into metadata driver, cloud data placement and mapping mechanism for research. We decompose the personalized technologies into metadata drive, cloud data placement, and mapping mechanism. In order to solve the problem that traditional personalization customization is unable to be applied in the SaaS field, we propose a multi-tenant personalized warehousing mode architecture, designed a personalization warehouse management platform based on SaaS model, and realized SaaS-based data isolation, interface customization, rapid positioning, and on-demand customization services. Experimental results show that the proposed multi-tenant personalized warehouse model can achieve data isolation and customization, and reflect the advantages of highly automated warehousing, shared storage resources, and on-demand customization in terms of warehouse management, data security, and user experience. © 2022 IEEE.

关键词： Metadata

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Minimization of Trim Loss During Reel Cutting at Paper Mill by Using Different Optimization Algorithms 2nd

Minimization of Trim Loss During Reel Cutting at Paper Mill ...

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2nd International Congress on Advances in Mechanical and Systems engineering, CAMSE 2021

作者： Srivastava, Manish Pati, Smitarani Verma, Om Prakash Sharma, Tarun Kumar Gupta, Himanshu Arya, Raj Kumar Tiwari, Anurag Kumar Sahu, Deepak Department of Instrumentation and Control Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar144011 India Department of Computer Science and Engineering Shobhit University Saharanpur India Department of Chemical Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar144011 India

ISBN: (纸本)9789811921872

Trim loss is one of the major issues in the paper industry and occurs during the cutting of master and stocked reels to fulfill the ordered demands of reels with smaller widths. The trims (paper waste) produced during this reel cutting need to be reprocessed and follow a heavy chemical process that causes a significant amount of effluent discharge to the water surface which is hazardous as per environmental concern. Hence, this work aims to reduce the trim loss problem by using the flexible width master reels and stocked over-product and usable leftover reels. The minimization is performed with a linear single objective optimization problem with consideration of different operational and technological constraints. Three different solution approaches named simplex method, particle swarm optimization, and genetic algorithm have been proposed to optimize this trim loss problem employed for solving a real-world industrial problem. Again, the obtained solutions are analyzed in contrast with some reported results to prove the validity of the model and check the efficiency of the algorithms. The optimized result produces minimization in trim production due to which a lesser reproduction required that depletes the chemical use and tends to economic saving and reduction in environmental pollution. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks 2

Residual Network and Embedding Usage: New Tricks of Node Cla...

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2nd International Conference on computer, Big Data and Artificial Intelligence, ICCBDAI 2021

作者： Chi, Huixuan Wang, Yuying Hao, Qinfen Xia, Hong Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks. In the literature, however, most tricks or techniques are either briefly mentioned as implementation details or only visible in source code. In this paper, we first summarize some existing effective tricks used in GCNs mini-batch training. Based on this, two novel tricks named GCN_res Framework and Embedding Usage are proposed by leveraging residual network and pre-trained embedding to improve baseline’s test accuracy in different datasets. Experiments on Open Graph Benchmark (OGB) show that, by combining these techniques, the test accuracy of various GCNs increases by 1.21%∼2.84%. We open source our implementation at https://***/ytchx1999/PyGOGB-Tricks. © 2022 institute of Physics Publishing. All rights reserved.

关键词： Convolution

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Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning

arXiv

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arXiv 2024年

作者： Krishnamurthy, Vikram Rojas, Cristian R. School of Electrical and Computer Engineering Cornell University United States Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measurement of the conditional mean of the previous Kalman filter. The prior is updated by the m-th Kalman filter. When m = 2, and the observations are noisy measurements of a Gaussian random variable, the covariance goes to zero as k−1/3 for k observations, instead of O(k−1) in the standard Kalman filter. In this paper we prove that for m agents, the covariance decreases to zero as k−(2m−1), i.e, the learning slows down exponentially with the number of agents. We also show that by artificially weighing the prior at each time, the learning rate can be made optimal as k−1. The implication is that in word-of-mouth social learning, artificially re-weighing the prior can yield the optimal learning rate. Copyright © 2024, The Authors. All rights reserved.

关键词： Kalman filters

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Frequency Domain Auto-tuning of Structured LPV controllers for High-Precision Motion control

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory HUNREN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

关键词： Technological innovation Sensitivity Frequency-domain analysis Stability criteria Prototypes Throughput Frequency response Motion control Optimization MIMO communication

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ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection 41

ESNet: Evolution and Succession Network for High-Resolution ...

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41st International Conference on Machine Learning, ICML 2024

作者： Liu, Hongyu Cong, Runmin Li, Hua Xu, Qianqian Huang, Qingming Zhang, Wei Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature;the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24. Copyright 2024 by the author(s)

关键词： Miocene

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Unsupervised Learning for Wafer Surface Defect Pattern Recognition

Unsupervised Learning for Wafer Surface Defect Pattern Recog...

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Chinese Intelligent Automation Conference, CIAC 2021

作者： Geng, Sheng Liu, Huaping Wang, Feng Zhao, Shimin Liu, Hu Department of Control Science and Engineering Shanghai Institute of Technology Shanghai201418 China Department of Computer Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9789811663710

With the development of the semiconductor industry, the demand for wafer production has gradually increased. Wafer manufacturing is a very complicated process, and any abnormal fluctuations in each process in this process may cause surface defects on the wafer. Accurate and rapid identification of wafer defect patterns can promptly reflect abnormal problems in the production process. Aiming at such tasks, this paper proposes a pattern recognition method for wafer surface defects based on unsupervised learning. The method is divided into two parts: unsupervised pre-training and classification fine-tuning. In the unsupervised pre-training stage, in order to improve the model’s surface defect feature extraction capability, we propose a new wafer-oriented unsupervised sampling method (WaUSM). Our wafer surface defect pattern recognition method uses an unsupervised pre-training model as the initialization to set up a classification model downstream, and fine-tune the classification model through a small number of label images with wafer defect patterns, so that the classification model can more accurately identify various types of defects pattern. The method we proposed was successfully verified by wafer defect pattern recognition on the public dataset WM-811K, and the experimental results fully proved the effectiveness and industrial applicability of the method we proposed. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unsupervised learning

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