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8th International Conference on Electrical, Mechanical and Computer engineering, ICEMCE 2024

作者： Chen, Zhigang Cui, Zhenfei Yang, Liyong Tong, Chaonan University of Science and Technology School of Automation and Electrical Engineering Beijing China North China University of Technology College of Electrical and Control Engineering Beijing China

ISBN: (纸本)9798331506230

Integrating filters into inverters to improve the power quality is essential. This study examines a three-phase dual-frequency grid-connected inverter designed to minimize switching losses by reducing the switching frequency in the energy transmission channel. The system utilizes L-filters and auxiliary units (AUs) to suppress harmonics and ensure high-quality grid-connected current, effectively addressing resonance issues associated with LCL filters. Simulations and experimental results show that this scheme could eliminate the circulating current between the two units and effectively suppress the leakage current. © 2024 IEEE.

关键词： Switching frequency

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Path Planning Using Improved Hybrid A∗ Algorithm for Mobile Robots 25

Path Planning Using Improved Hybrid A∗ Algorithm for Mobile...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Cheng, Zikang Xue, Jingbo Wang, Bo Dong, Guangzhong Wei, Jingwen Chen, Chunlin Nanjing University Department of Control Science and Intelligence Engineering Naning China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350366600

The Hybrid A∗ algorithm is suitable for Ackermann-type mobile robots with nonholonomic constraints. However, in practical path planning, such issues as long search times, inefficient search efficiency, and excessive planning path changes causing unstable robot motion still exist. To improve the effectiveness of path planning, this paper optimizes the Hybrid A∗ algorithm by using variable search step size and designing a path evaluation function during node expansion. Path planning experiments are conducted based on simulation and physical experimental platforms. The results show that the improved algorithm reduces the search nodes and planning time, effectively enhancing the algorithm's search performance and efficiency. In addition, it avoids pose errors caused by reverse driving, ensuring the priority and smoothness of forward driving, and achieves efficient and stable path planning for Ackermann-type mobile robots. © 2024 IEEE.

关键词： Mobile robots

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Improvement of polypropylene/silicone rubber interface by insulating oils with pressure optimization

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IEEE Transactions on Dielectrics and Electrical Insulation 2025年第3期32卷 1289-1296页

作者： Luo, Zhaorui Chu, Jincheng Wang, Liyan Lu, Tianhe Tian, Zhengbing Li, Zhonglei Fang, Zhi Zhu, Xi Nanjing Tech University College of Electrical Engineering and Control Science Jiangsu Nanjing211816 China ZTT Cable Accessories Co. Ltd Jiangsu Nantong226010 China Tianjin University School of Electrical Automation and Information Engineering Tianjin300072 China

Cable accessory insulation system is inevitably affected by its interface states causing insulation failure. Insulating oils are often applied in the interface with a certain pressure to improve its performance, but the mismatching and degradation of polymer in insulating oils seriously affects the interface stability. This study focuses on polypropylene (PP) insulation and aims to improve its typical accessory interface with silicone rubber (SIR) by insulating oils with pressure. Results show that hydrocarbon oil has the biggest negative impact on PP with the most mass increment, more surface deposits and significant deteriorating in both mechanical and electrical properties. By contrast, appropriate absorption of Si-containing oil helps modify surface and fill initial defects of PP, promoting insulating performance. Furthermore, it is found that interface pressure is conductive to fabricate a stable PP/insulating oil/SIR structure with excellent insulating performance. However, excessive pressure causes a negative impact due to interface deformation of materials. Based on the analysis of interface microstructure and the calculation of contact stress between metal electrode and polymer, the mechanism of coupling interaction among polymer, insulating oil and external pressure is revealed. This research on the improvement of insulation interface can provide a key reference and basis for the manufacturing and optimizing of cable insulation. © 1994-2012 IEEE.

关键词： Silicone rubber

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Dynamic Accuracy Optimization for NC controlled Industrial Robots 28

Dynamic Accuracy Optimization for NC controlled Industrial R...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Mandiola, Asier Armendia, Mikel Gonzalez, Diego Eguskiza, Jon Automation and Control Unit TEKNIKER Eibar Spain Mechanical Engineering Unit TEKNIKER Eibar Spain

ISBN: (纸本)9798350339918

In the last years the usage of industrial robotic manipulators is being extended to new applications, like laser or machining-based manufacturing. These applications require new user interface functionalities coming from common NC control systems, as well as increased demands in path tracking, dynamics, and accuracy. In this paper, a Dynamic Accuracy Optimization strategy is applied on a NC controlled industrial manipulator to minimize robot Tool Center Point errors during path execution. A state-of-the-art laser tracker system is used for online characterization of the TCP position which is fed to the compensation algorithm integrated in the NC controller. A drastic reduction of static and dynamic errors has been observed in both linear and orientation degrees of freedom, impacting also in the resulting path errors. © 2023 IEEE.

关键词： Errors

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Event-Triggered Distributed Intelligent Learning control of Six-Rotor UAVs under FDI Attacks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3299-3312页

作者： Wu, Ying Chen, Mou Li, Hongyi Chadli, Mohammed Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China University Paris-Saclay Univ Evry IBISC Evry91020 France Guangdong University of Technology School of Automation The Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China

Aiming at the six-rotor unmanned aerial vehicles (UAVs) subjected to false data injection (FDI) attacks, an event-triggered-based distributed intelligent learning control strategy is proposed in this article. The reinforcement learning algorithm which is designed based on neural networks (NNs) is introduced to achieve intelligent optimal control. Under the actor-critic-identifier frame, three kinds of NNs are used to realize the control action, evaluate the system performance, and estimate the unknown dynamic, respectively. Then, an improved event-triggered strategy including a decreasing function of the consensus error is designed to reduce the waste of resources while decreasing the adverse impact on tracking control performance as far as possible, which also does not exhibit Zeno behavior. Furthermore, an adaptive compensation control scheme is given, which can effectively compensate for the negative impacts brought by the FDI attacks existing in information interaction among UAVs. Despite the impact of lumped disturbances and FDI attacks, the proposed disturbance-observer-based distributed intelligent learning control strategy can still guarantee that all signals in the closed-loop UAV systems are bounded, and all follower UAVs can track the signal of the leader UAV. Finally, some simulation verification diagrams are shown to test the feasibility of the designed control strategy. © 2020 IEEE.

关键词： Neural networks

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One-Variable Attack on the Industrial Fault Classification System and Its Defense

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engineering 2022年第12期19卷 240-251页

作者： Yue Zhuo Yuri A.W.Shardt Zhiqiang Ge State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Department of Automation Engineering Technische Universität IlmenauIlmenau D-98684Germany

Recently developed fault classification methods for industrial processes are mainly ***,models based on deep neural networks have significantly improved fault classification accuracy owing to the inclusion of a large number of data ***,these data-driven models are vulnerable to adversarial attacks;thus,small perturbations on the samples can cause the models to provide incorrect fault *** recent studies have demonstrated the vulnerability of machine learning methods and the existence of adversarial *** paper proposes a black-box attack method with an extreme constraint for a safe-critical industrial fault classification system:Only one variable can be perturbed to craft adversarial ***,to hide the adversarial samples in the visualization space,a Jacobian matrix is used to guide the perturbed variable selection,making the adversarial samples in the dimensional reduction space invisible to the human *** the one-variable attack(OVA)method,we explore the vulnerability of industrial variables and fault types,which can help understand the geometric characteristics of fault classification *** on the attack method,a corresponding adversarial training defense method is also proposed,which efficiently defends against an OVA and improves the prediction accuracy of the *** experiments,the proposed method was tested on two datasets from the Tennessee–Eastman process(TEP)and steel plates(SP).We explore the vulnerability and correlation within variables and faults and verify the effectiveness of OVAs and defenses for various classifiers and *** industrial fault classification systems,the attack success rate of our method is close to(on TEP)or even higher than(on SP)the current most effective first-order white-box attack method,which requires perturbation of all variables.

关键词： Adversarial samples Black-box attack Industrial data security Fault classification system

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Parameters Setting of Firefly Algorithm

Parameters Setting of Firefly Algorithm

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Chang Lu, Yong Zhang, Lina Fan, Liyun Harbin Engineering University Harbin China Beijing Automation Control Equipment Institute Beijing China

ISBN: (纸本)9789811966125

Parameter setting is one of the long-standing grand challenges of the metaheuristic algorithm filed. The effect of the optimization algorithm will mainly depend on the setting of the algorithm-dependent parameters. The best result for solving the optimization problems can be achieved by the optimal setting of the algorithm’s parameter. In this paper, we investigate the parameter setting problem of firefly algorithm. The sufficient simulation results are showed that with proper setting of the parameter firefly algorithm can converge efficiently and accurately. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

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Optimal Scheduling of an Independent Electro-Hydrogen System with Hybrid Energy Storage Using a Multi-Objective Standardization Fusion Method

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Energy engineering 2025年第1期122卷 63-84页

作者： Suliang Ma Zeqing Meng Mingxuan Chen Yuan Jiang School of Electrical and Control Engineering North China University of TechnologyBeijing100144China ChinaThree Gorges Technology Co. Ltd.Beijing100032China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China

In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is ***,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical *** deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s *** optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization *** proposed method better balances all optimization objective functions and reduces the impact of their *** the cost of BESS decreases by approximately 30%,its participation deepens by about 1 ***,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase *** study aims to provide a more reasonable approach to solving multi-objective optimization problems.

关键词： Electro-hydrogen system multi-objective optimization standardization method hybrid energy storage system

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The Study of Materials for Electric Field Protection of Power Transformer Testing 9

The Study of Materials for Electric Field Protection of Powe...

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9th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2023

作者： Meesuk, Peerawat Bunpakdee, Prajak Sorn-In, Sirirat Bansomdejchaopraya Rajabhat Univrtsity Electrical Engineering and Automation Control System Program Faculty of Engineering and Industrial Technology Bangkok Thailand

ISBN: (纸本)9798350322040

This paper proposes the analysis of the material can be protected from transformer testing and presents a mathematical model of the power transformer. In this research, transformers were study in four protective materials, wood, rubber, glass and acrylic that are used in between the electric field measurement and the transformer. By simulating the test results of a transformer with a voltage of 230 kV. Computer-based simulation utilizing the finite element method (FEM) is exploited as a tool for visualizing electric fields distribution volume a power transformer. The simulation results showed that the material with the best protection against the electric field was wood insulation and the best installation location was a distance of 5 m from the transformer. © 2023 IEEE.

关键词： Finite element method

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GRU combined model based on multi-objective optimization for short-term residential load forecasting

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

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