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Performance Comparison of Distributed State Estimation Algorithms for Power Systems

Journal of Systems science & Complexity 2017年第3期30卷 595-615页

作者： SUN Yibing FU Minyue ZHANG Huanshui School of Control Science and Engineering Shandong University School of Electrical Engineering and Computer Science University of Newcastle School of Automation Guangdong University of Technology

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori(MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.

关键词： Distributed MAP estimation distributed state estimation extended Kalman filter power systems.

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Highway self-contained multi-microgrid energy management strategy based on universal gravitation

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Energy 2025年 327卷

作者： Zhang, Lingzhi Shi, Ruifeng Ma, Xiaolei Jia, Limin Lee, Kwang Y. School of Control and Computer Engineering North China Electric Power University Beijing102206 China China Institute of Energy and Transportation Integrated Development North China Electric Power University Beijing102206 China School of Transportation Science and Engineering Beihang University Beijing100191 China State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Beijing100044 China Department of Electrical and Computer Engineering Baylor University WacoTX76798 United States Yonsei Frontier Lab Yonsei University Seoul03722 Korea Republic of

Energy acts as a crucial driving force for transportation, while transportation functions as a significant role within the energy systems. Both sectors share the vital responsibility of enabling a low-carbon transition. The advancement of clean energy and the establishment of green transportation are the keys to achieving sustainable, low-carbon transformation of energy and transportation systems. This study addresses the challenges of energy management strategies within the nexus of energy and transportation, specifically targeting off-grid regions in Western China, where conventional power infrastructure is lacking and road traffic is critical. A two-tiered energy management approach is proposed for interconnected self-contained multi-microgrid (MMG) systems along road networks, inspired by the principles of gravitational law. The proposed framework consists of two phases: the energy exchange among microgrids (MGs) and the charging and discharging of individual MG energy storage systems (ESSs). This structure effectively mitigates the uncertainties inherent in renewable energy sources and load demands. A gravitational scheduling model is first developed by drawing analogies between the elements within the MGs and gravitational principles, determining energy exchanges at the MMG level. Following this, the ESS charging and discharging processes are then dictated by the remaining power imbalance. By optimizing the sequence and hierarchy of energy device interactions, this strategy minimizes operational costs while maximizing the system's self-contained capability. Simulation results provide compelling evidence of the effectiveness of the proposed energy management strategy in reducing operational costs and enhancing system self-contained performance, particularly in remote, off-grid areas of Western China. © 2025 Elsevier Ltd

关键词： Strategic planning

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Nonlinear Bandwidth and Bode Diagrams based on Scaled Relative Graphs

arXiv

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arXiv 2025年

作者： Krebbekx, Julius P.J. Tóth, Roland Das, Amritam Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Lab HUN-REN Institute for Computer Science and Control Budapest Hungary

Scaled Relative Graphs (SRGs) provide a novel graphical frequency domain method for the analysis of nonlinear systems. In this paper, we use the restriction of the SRG to particular input spaces to compute frequency-dependent gain bounds for incrementally stable nonlinear systems. This leads to a nonlinear (NL) generalization of the Bode diagram, where the sinusoidal, harmonic, and subharmonic inputs are considered separately. When applied to the analysis of the NL loop transfer and sensitivity, we define a notion of bandwidth for both the open-loop and closed-loop, compatible with the LTI definitions. We illustrate the power of our method on the analysis of a DC motor with a parasitic nonlinearity, verifying our results in simulations. © 2025, CC BY.

关键词： Frequency domain analysis

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Chinese Journal of Electronics 2021年第5期30卷 876-884页

作者： QIAO Sibo PANG Shanchen WANG Min ZHAI Xue DAI Feng College of Computer Science and Technology China University of Petroleum College of Control Science and Engineering China University of Petroleum College of Information Science and Engineering Shandong University of Science and Technology

Popularity prediction of online video is widely used in many different scenarios. It can not only help video service providers to schedule video web sites,but also bring considerable profits on investment for both providers and advertisers if popularity of online video is predicted accurately. However, online video popularity prediction still cannot have a satisfactory result, due to the complexity of many crucial factors especially of video distribution network. In this article, we extract seven factors from huge amounts of data about user behavior,establishing a new multiple linear regression model to initially predict online video popularity. After that, a multichannel video popularity dynamic scheduling model is proposed to schedule videos on which channel and what time to be broadcast, according to its popularity predicted by multiple linear regression model, ensuring that maximum the sum value of online video popularity of each channel. Experimental results on dataset obtained from Sohu Video, a video service provider in China, and real-world video flow in Sohu Video demonstrate that the proposed model is robust and has promising performance in predicting online video popularity, which is helpful for video service providers to schedule videos on web sites effectively in the future.

关键词： regression analysis video communication Internet video signal processing Web sites real-world video flow online video popularity regression prediction model video service provider Sohu Video video distribution network user behavior video Web sites dynamic scheduling multichannel video popularity dynamic scheduling model multiple linear regression model

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Consistent, highly throughput and space scalable distributed architecture for layered NoSQL data store

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Scientific reports 2025年第1期15卷 19172页

作者： Adam Krechowicz Stanisław Deniziak Grzegorz Łukawski Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland. a.krechowicz@tu.kielce.pl. Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland.

Maintaining strong consistency and throughput in distributed NoSQL systems is very important these days, but often impossible to achieve at the same time. Consistency problems in distributed systems result in serious consequences, e.g. data loss, while throughput problems lead to poor system performance. This paper goes beyond solving consistency issues in distributed NoSQL systems and addresses the important problem of ensuring high throughput in such systems at the same time. To this end, we proposed a novel architecture of the layered NoSQL system that enables greater throughput by using replication of data items in a dynamic way while still preserving strong consistency. It is characterized by high availability, enhanced throughput, strong consistency, and space scalability. This system was built on top of a very efficient NoSQL system, called Scalable Distributed Two-Layer Data Store (SD2DS). To develop our system, we identified and analyzed the inconsistencies in the case of SD2DS architecture with increased throughput in the case of concurrent operations execution, as well as in the case of unfinished operations. The theoretical correctness of the proposed solution was proved. Its performance was experimentally evaluated in comparison with common NoSQL systems such as MemCached and MongoDB. The results confirmed its superiority in terms of performance, so it can successfully compete with publicly available solutions. It makes it possible to use the SD2DS system in practical IT systems that require high performance and consistency.

关键词： Big data Consistency Data replication NoSQL Scalability Throughput

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Adaptive ELM-Based Time-Constrained control of Uncertain Robotic Manipulators With Minimum Learning Computation

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IEEE Transactions on Emerging Topics in Computing 2025年

作者： Jin, Xiaozheng Hou, Yuhan Wu, Xiaoming Chi, Jing Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Shandong Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Jinan250013 China Qilu Institute of Technology School of Intelligent Manufacturing and Control Engineering Shandong Jinan250200 China Shandong University of Finance and Economics School of Computing and Artificial Intelligence Shandong Jinan250014 China

This paper studies the extreme learning machine (ELM)-based time-constrained trajectory tracking control of a class of robotic manipulator systems with model/input uncertainties, matched and mismatched disturbances. A uniform robust exact differentiator (URED) is developed to construct a multi-layer virtual control framework of the robotic manipulator system. Under the control framework, adaptive ELM-based control strategies are proposed to suppress the influence of the uncertainties and disturbances layer-by-layer, combining with the minimum learning parameter (MLP) technique which is employed to reduce the calculation complexity of ELM parameters. The significance of this study is that general model/input uncertainties, matched and mismatched disturbances can be effectively compensated within a limited time, so that bounded trajectory tracking of the robotic manipulator can be achieved avoiding the complexity explosion issue. The time-constrained stability of the closed-loop robotic error systems is proved through Lyapunov stability theory. Finally, comparative simulations are employed to display the feasibility and superiority of the designed robust adaptive ELM-based control schemes of a robotic manipulator system. © 2013 IEEE.

关键词： Robust control

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LEARNING OF MODULAR STRUCTURED NETWORKS

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ARTIFICIAL INTELLIGENCE 1995年第1期75卷 51-62页

作者： ISHIKAWA, M Department of Control Engineering and Science Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka 820 Japan

Learning of large-scale neural networks suffers from computational cost and the local minima problem. One solution to these difficulties is the use of modular structured networks. Proposed here is the learning of modular networks using structural learning with forgetting. It enables the formation of modules. It also enables automatic utilization of appropriate modules from among the previously learned ones. This not only achieves efficient learning, but also makes the resulting network understandable due to its modular character. In the learning of a Boolean function, the present module acquires information from its subtask module without any supervision. In the parity problem, a previously learned lower-order parity problem is automatically used. The geometrical transformation of figures can be realized by a sequence of elementary transformations. This sequence can also be discovered by the learning of multi-layer modular networks. These examples well demonstrate the effectiveness of modular structured networks constructed by structural learning with forgetting.

关键词： Learning systems

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Path Planning for Coverage Spraying of Plants in Outdoor Wheeled Mobile Robots

Path Planning for Coverage Spraying of Plants in Outdoor Whe...

引用

Robotics, control and Automation (ICRCA), International Conference on

作者： Weixin Zhang Zhengxin Yu Shixin Mao Xuefeng Zhou Jia Pan Haifei Zhu School of ElectRomechanical Engineering Guangdong University of Technology Guangzhou China Jiutian Innovation (Guangdong) Intelligent Technology Co Ltd Foshan China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangzhou China Department of Computer Science The University of Hong Kong Hong Kong China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

In contemporary agricultural practices and pest management, the deployment of outdoor wheeled mobile robots for precise and efficient plant spraying is crucial to optimize chemical application and mitigate environmental impact. This study introduces an integrated path planning framework designed to systematically tackle the challenges of obstacle avoidance, adherence to kinematic constraints, and optimization of spraying operations, while ensuring complete coverage of target plants. The framework comprises three key components: a local route generator utilizing principal component analysis to minimize movement required for spraying, thereby enhancing efficiency; a global path optimizer that effectively sequences and connects the generated routes to produce collision-free paths; and a path regulator that fine-tunes the resulting paths to comply with the robot's kinematic constraints. Extensive simulations across various outdoor scenarios demonstrate that the proposed framework achieves comprehensive coverage, reduces path lengths, and improves operational efficiency, presenting a viable solution for advanced robotic spraying applications.

关键词： Regulators Robot kinematics Spraying Kinematics Path planning Real-time systems Mobile robots Collision avoidance Optimization Principal component analysis

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drug-target interactions Signed heterogeneous network Link sign prediction Graph neural networks

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Networked automatic test system based on message-oriented middleware

International Journal of Control and Automation

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International Journal of control and Automation 2015年第3期8卷 147-160页

作者： Fengguang, Xiong Xie, Han Computer Science and Control Engineering North University of China Taiyuan China

According to the current status of automatic test system which focuses only on a single or the same type of weapons' performance testing, a networked automatic test system based on message-oriented middleware is proposed in this paper, and inner architecture and process of pus/sub in message-oriented middleware are described. Basing on the message-oriented middleware, the networked automatic test system can shield the diversity and complexity of the bottom test system and test equipment, and can implement cross-platform communication of various test data about weapons. In addition, based on Kerberos protocol, the authentication process ensures the reliability of message publish/subscribe. Experiments show that the networked automatic test system based on message-oriented middleware is an integrated test platform which can provide comprehensive performance test for coordinated engagement on a variety of weapons. © 2015 SERSC.

关键词： Middleware

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