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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Zhao, Chunhui Li, Danli Zhang, Jiyong Yu, Gao Yan, Jiangyu Wang, Hong Bo, Yulian State Grid Economic and Technological Research Institute Co. Ltd. Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350333664

Predictive power data services are an effective way to unleash the value of power data. In response to the current lack of effective evaluation for such services, this paper proposes an evaluation system and method for assessing the quality of predictive power data services. The objective is to enhance service quality, improve service benefits, and provide better decision support and management tools for the power industry. The proposed approach is based on the cloud model principle. The golden section method is employed to generate the cloud, while the improved entropy weight method is used to calculate the weights. The effectiveness of the proposed evaluation method is validated through the evaluation of predictive power data services provided in different regions. © 2023 IEEE.

关键词： cloud model data services improved entropy weight method service evaluation

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Comprehensive Evaluation of Power Business Data Service Based on Indicator Simplification and Weights Fusion 7

Comprehensive Evaluation of Power Business Data Service Base...

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7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Zhao, Chunhui Li, Danli Zhang, Jiyong Yu, Gao Yan, JiangYu Zhai, WeiTeng State Grid Economic and Technological Research Institute Co. Ltd. Beijing China North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9798350334197

Power business data services explore the potential value of power data by analyzing and mining power big data to assist in the development of new power systems and smart grids. This paper looks into the potential of power data by exploring power business data services. To evaluate the service, we consider four aspects: service benefit, data quality, service quality, and data service performance. The DEMATEL-ISM method is used to simplify the indicator system. Additionally, the DEMATEL method is combined with the AHP and coefficient of variation methods to form a subjective-objective combination of weighting methods for determining the weights of the indicators. This method addresses the lack of objectivity in the weights caused by the interaction between indicators and the overlap of meanings. The proposed method is validated through examples to show its feasibility and validity. © 2023 IEEE.

关键词： Smart power grids

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An Adaptive Fault-Tolerant control Without Fault Location of Open-Phase Fault for Dual Three-Phase PMSM Drive System

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Liu, Qi Xiao, Lan Wu, Qunfang Zhao, Xiaopeng Liu, Ying Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211100 China Avic Xi'an Flight Automatic Control Research Institute Xi'an710000 China

An adaptive fault-tolerant control (FTC) method without fault localization is proposed for the common open-phase faults (OPFs) in dual three-phase permanent magnet synchronous motor (DTP-PMSM) drive systems. The method eliminates the need for fault localization through fault diagnosis, thus reducing the risk of misdiagnosis. The operational state of the DTP-PMSM under OPF is analyzed and a uniform reference current with fault current angle is established in the dual dq coordinate system. After an OPF occurs, the unified current reference can be directly applied to the drive system without fault localization. The fault current angle is acquired by Phase-Locked Loop (PLL), and can still be well acquired even under light load condition. Compared with the existing PLL-based adaptive fault tolerance scheme, one PLL loop is reduced, which reduces the computational burden. The proposed adaptive FTC scheme does not require adjustment of the control framework, machine model and transformation matrix before and after the OPF, and the switching between minimum copper loss, maximum torque output and healthy operation can be achieved by adjusting the amplitude coefficient of the reference current. Experimental results verify the effectiveness of the proposed fault-tolerant control scheme. © 2025 IEEE.

关键词： Permanent magnets

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Reliable Navigation Learning in Stochastic Transportation Networks with Uncertain Topology 3

Reliable Navigation Learning in Stochastic Transportation Ne...

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3rd International Conference on Pattern Recognition and Machine Learning, PRML 2022

作者： Guo, Hongliang Shi, Rui Deng, Yiran Chen, Qiming Zhou, Yingjie Institute for Infocomm Research Agency for Science Technology and Research Singapore Singapore School of Automation Engineering Chengdu China College of Computer Science Chengdu China College of Communication Engineering Chengdu China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

This paper studies the reliable navigation problem in stochastic transportation networks with uncertain topology. The objective is to find a dynamic routing policy, which navigates the ego vehicle to the destination with the minimal linear combination of mean and standard deviation (mean-std) of travel time. Different from almost all other stochastic routing problems, which focus on the stochasticity of travel time and assume a fixed topology of the underlying transportation network, the reliable navigation problem considered in this paper involves an additional layer of stochasticity, namely the uncertain network topology. To reach reliable navigation, we advance the canonical reinforcement learning (RL) method, which could originally find a routing policy with the minimal mean travel time, to simultaneously estimate and minimize the linear combination of the mean and standard deviation of a routing policy's travel time. Additionally, to cope with the uncertain network topology problem, we enhance RL's underlying Markov decision process (MDP) with a variational action set as well as a novel decision-list policy that outputs a list of ranked actions instead of a single one. We evaluate and compare the proposed method with state-of-the-art mean-std shortest path solutions in a range of transportation networks, and demonstrate that the proposed method achieves superior performance with the lowest response time. © 2022 IEEE.

关键词： Travel time

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research on Intelligent Management and Assisted Decision Making Technology of Electric Power research Enterprise Based on Knowledge engineering 24

Research on Intelligent Management and Assisted Decision Mak...

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3rd International Conference on Artificial Intelligence and Education, ICAIE 2024

作者： Zhang, Baoliang Xu, Yinghui Li, Chengyuan Jiang, Yuan Cui, Wenchao Yue, Hongxu Hui, Chen Hu, Ziwei Digitisation Department China Electric Power Research Institute Beijing China School of Mechanical and Electrical Engineering China University of Mining and Technology Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798400712692

Currently, the internal management knowledge of electric power research enterprises is difficult to integrate and structured organization, resulting in greatly reduced decision-making efficiency. Knowledge Graph(KG), as an efficient knowledge organization, helps to connect the complex knowledge network. However, for a Q&A platform based solely on knowledge graphs, it can be challenging to interpret and analyze natural language input, especially when considering historical Q&A data. In this paper, we combine the KG with a Large Language Model(LLM), choose the ERNIE model fine-tuned by the text of electric power domain knowledge, and use the TransE method to integrate the KG into the model's structure to build a knowledge-based Q&A system that assists researchers in decision-making. The experimental results show that the ERNIE model combined with KG outperforms the comparison model in terms of precision, recall, and F1 value in entity and relation classification tasks, and the performance is further improved by increasing the number of attention heads. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Risk perception

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Review of Inference Time Prediction Approaches of DNN: Emphasis on Service robots with cloud-edge-device architecture

Review of Inference Time Prediction Approaches of DNN: Empha...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Xiang, Tian Meng, Qiwei Zhang, Ji Zhang, Beibei Song, Wei Xie, Anhuan Gu, Jason Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China The Chinese University of Hong Kong T Stone Robotics Institute Department of Mechanical and Automation Engineering Hong Kong Research Institute of Intelligent Computing Zhejiang Laboratory Research Center for Intelligent Computing Software Hangzhou311100 China Dalhousie University Electrical and Computer Engineering Halifax Canada

ISBN: (纸本)9798350325706

In recent years, the global robot market has witnessed substantial growth, particularly in the domain of service robots. Despite their expanding presence, service robots encounter limitations when operating autonomously in unstructured environments, primarily due to their constrained computational capacities. As a solution, the fusion of cloud and edge computing resources becomes imperative to expedite task inference and enhance scenario perception capabilities. The integration of cloud-edge-device models holds significant promise in bolstering the operational efficiency of robots. This entails the dynamic partitioning of intricate robotic tasks, executed collaboratively across cloud, edge, and device resources. In this landscape, deep neural network (DNN) models play a pivotal role in facilitating a wide array of robotic tasks. The inference time for each layer of a DNN model in actual deployment, emerges as a critical determinant in the model's partitioning strategy. It also serves as an important metric influencing the model's suitability for a specific hardware platform. This article presents an overview of recent advancements in predicting inference and training time of DNN models, summarizes the related methods, and finally discusses the challenges in this field and the research that can be studied in the future. © 2023 IEEE.

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Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 75-89页

作者： Aijuan Song Guohua Wu Witold Pedrycz Ling Wang School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland Department of Automation Tsinghua UniversityBeijing 100084China

Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple *** algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one ***,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used *** contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve *** VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation *** enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the *** test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,*** results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared ***,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.

关键词： Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)

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Design and locomotion characteristic analysis of a novel tensegrity hopping robot

Design and locomotion characteristic analysis of a novel ten...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Mo, Jixue Gao, Changqing Fang, Hao Yang, Qingkai Peng Cheng Laboratory Department of Strategic and Advanced Interdisciplinary Research Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Beijing Institute of Technology School of Automation Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9798350325706

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot's hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment. © 2023 IEEE.

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Formation control of Heterogeneous Multi-Agent Systems Under Fixed and Switching Hierarchies

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IEEE Access 2024年 12卷 97868-97882页

作者： Shamrooz Aslam, Muhammad Bilal, Hazrat Chang, Wen-Jer Yahya, Abid Anjum Badruddin, Irfan Kamangar, Sarfaraz Hussien, Mohamed China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou221116 China University of Science and Technology of China Department of Automation Hefei230026 China Department of Marine Engineering Keelung202 Taiwan Botswana International University of Science and Technology Department of Electrical Computer and Telecommunications Engineering Palapye Botswana King Khalid University College of Engineering Department of Mechanical Engineering Abha Saudi Arabia King Khalid University Faculty of Science Department of Chemistry Abha61413 Saudi Arabia

Modern information technology is driving the rapid development of the information and automation industry through the combination of computer technology, communication technology, and control technology. Inspired by nature's cluster movement, such as birds, people proposed the concept of Multi-Agent Systems (MASs). This paper deals with the formation control problem for a class of heterogeneous multi-agent systems with time-delays. First, the formation control of heterogeneous multi-agent systems with communication delay in fixed and switching topologies is investigated. A heterogeneous multi-agent system model with input delay and communication delay is established. Furthermore, based on this model, the formation control protocol is designed and the stability of the proposed control protocol in fixed and switched topologies is analyzed. The first- and second-order multi-agent control system was formulated for both fixed and switched topology, respectively. Then, using the new LMI toolbox, the feasibility of the parameters is obtained and the example is created by MATLAB. The simulation results show that the proposed formation control protocol with delay in this paper can make the systems converge to the expected value under fixed and switched hierarchies. © 2013 IEEE.

关键词： Topology

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Model predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation 63

Model predictive control for tracking using artificial refer...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Krupa, P. Kohler, J. Ferramosca, A. Alvarado, I. Zeilinger, M.N. Alamo, T. Limon, D. Computer Science Group L'Aquila Italy Institute for Dynamic Systems and Control Eth Zürich ZürichCH-8092 Switzerland University of Bergamo Information and Production Engineering Department of Management Via Marconi 5 BG Dalmine24044 Italy Universidad de Sevilla Department of Systems Engineering and Automation Seville Spain

ISBN: (纸本)9798350316339

This paper provides a comprehensive tutorial on a family of Model Predictive control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision variables in the optimization problem. These formulations have several benefits with respect to the classical MPC formulations, including guaranteed recursive feasibility under online reference changes, as well as asymptotic stability and an increased domain of attraction. This tutorial paper introduces the concept of using an artificial reference in MPC, presenting the benefits and theoretical guarantees obtained by its use. We then provide a survey of the main advances and extensions of the original linear MPC for tracking, including its non-linear extension. Additionally, we discuss its application to learning-based MPC, and discuss optimization aspects related to its implementation. © 2024 IEEE.

关键词： Predictive control systems

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