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An improved calculation method for static capacitance in inductor windings

Progress In Electromagnetics Research C 2020年 104卷 25-36页

作者： Du, Mingxing Zhang, Yuxiao Wang, Hongbin Tian, Ye Ouyang, Ziwei Wei, Kexin Tianjin Key Laboratory of Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China

This paper proposes an improved method for calculating static capacitance between two conductors with circular cross-sections in inductor windings. It considers the effects of electric field coupling and energy distribution on static capacitance. In this paper, the capacitance between two conductors in inductor windings is calculated by the improved calculation method and finite-element method (FEM), respectively. The relative error of the improved calculation method is between 0.11% and 4.51% compared to the FEM. In order to verify the effectiveness of this method for inductor winding, the orthogonal stacking winding and staggered stacking winding are chosen as calculation examples to accurately predict the static capacitance of multi-layer circular-section induction coils. Finite element models for the two types of windings are built to determine the capacitances for our 3 × 3 array arrangement winding. The results show that the improved calculation method proposed in this paper highly conforms to FEM. Finally, we adopt an air-cored cylindrical inductor winding for experimental verification, and the improved calculation method is proved to be correct. © 2020, Electromagnetics Academy. All rights reserved.

关键词： Capacitance

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An Improved Levenberg-Marquardt Algorithm with Adaptive Learning Rate for RBF Neural Network 35

An Improved Levenberg-Marquardt Algorithm with Adaptive Lear...

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第35届中国控制会议

作者： AN Ru LI Wen Jing Han Hong Gui QIAO Jun Fei College of Electronic and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

In this paper,an improved Levenberg-Marquardt(LM) algorithm with adaptive learning rate is proposed to optimize the learning process of RBF neural ***,an improved LM algorithm is adopted using a quasi-Hessian matrix and gradient vector which are computed *** with the conventional LM algorithm,Jacobian matrix multiplication and storage are not required in the improved LM algorithm,which can reduce computation cost and solve the problem of memory ***,the adaptive learning rate is integrated into the improved LM algorithm in order to accelerate the convergence speed of training algorithm and improve the network performance of nonlinear system ***,several experiments are conducted and the results show that the proposed method has faster convergence speed and better prediction performance.

关键词： Improved LM algorithm RBF neural network adaptive learning rate fast convergence speed

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Design of a Self-organizing Recurrent RBF Neural Network Based on Spiking Mechanism 35

Design of a Self-organizing Recurrent RBF Neural Network Bas...

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第35届中国控制会议

作者： LU Chao HAN Honggui QIAO Junfei YANG Cuili College of Electronic and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

Based on the systemic investigation of recurrent neural network,a self-organizing recurrent radial basis function(SR-RBF) neural network which based on the spiking mechanism and improved Levenberg-Marquardt(LM) algorithm is proposed in this *** hidden neuron in the recurrent radial basis function(RRBF) can be added or pruned by computing the spiking strength of the connections between hidden and output neurons of RRBF neural ***,to ensure the accuracy of SR-RBF neural network,the parameters are trained by improved LM *** SR-RBF neural network is used for approximating the time-series prediction and classical non-linear ***,comparisons with other methods demonstrate that the SR-RBF neural network is more effective in terms of accuracy,generalization,and network structure.

关键词： Self-organizing spiking mechanism recurrent radial basis function time-series prediction

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Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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Research on conducted emi characteristics of sic mosfet considering temperature effect

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Progress In Electromagnetics Research C 2021年 112卷 69-82页

作者： Du, Mingxing Bian, Weiguo Wang, Hongbin Dai, Qiqi Ouyang, Ziwei Tianjin Key Laboratory of Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin300384 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China

—The junction temperature change of SiC MOSFET will change its switching process, and then affect the electromagnetic interference (EMI) characteristics of the system where the device is located and the safe operation of the surrounding equipment. Therefore, it is of great significance to research the temperature dependence of its EMI characteristics. In this paper, a buck converter composed of SiC MOSFET is taken as the research object to study the temperature variation characteristics of the conducted EMI spectrum during the switching process. Combined with the specific circuit connection form of the buck converter, the coupling paths of the conducted EMI are determined, and then the influence mechanisms of temperature change on the differential mode (DM) interference and common mode (CM) interference are analyzed. The theoretical analysis and experimental results show that the DM interference of the buck converter composed of SiC MOSFET increases with the increase of temperature, and the CM interference is almost unaffected by temperature. When the working temperature increases from 25◦C to 145◦C, the peak value of DM voltage increases by 6.7 dBµV, and the peak value of CM voltage changes less than 1.4 dBµV. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Temperature distribution

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Multi-objective Design of the Water Distribution systems Using SPEA2 35

Multi-objective Design of the Water Distribution Systems Usi...

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第35届中国控制会议

作者： MENG Qinchao QIAO Junfei YANG Cuili College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

As a complicated and combinatorial optimization problem, the design of Water distribution systems(WDSs) is difficult to be solved. In this paper, in order to design WDSs better, three objectives are considered, including the initial construction cost, the sum of node surplus head and the variance of node surplus head. The consideration of the variance of node surplus head can reflect the distribution of the node surplus head in WDSs. This problem is solved by the strength pareto evolutionary algorithm(SPEA2). Finally, the model is applied into two well-known benchmark case studies, the two-loop network and the New York Tunnels network. By comparing with some algorithms, such as Tabu search algorithm and non-dominated sorting genetiv algorithm(NSGA2), the performance of SPEA2 shows the effectiveness in terms of reliability, convergence, as well as diversity.

关键词： Multi-objective optimization Water distribution systems SPEA2

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Improved FastSLAM system Using Artificial Fish-Swarm Optimized Distributed Unscented Particle Filter 36

Improved FastSLAM System Using Artificial Fish-Swarm Optimiz...

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第36届中国控制会议

作者： Fujun Pei Hong Yan Mingju Zhu School of Electronic Information & Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781538629185

Particle impoverishment is inevitably induced because of the random particles prediction and resampling applied in particle filter,especially in SLAM problem with a large number of *** overcome these limitations,an improved FastSLAM system using artificial fish-swarm optimized distributed unscented particle filter（AFSO-DUPF） is developed in this *** main contribution of this paper is the derivation of AFSO-DUPF by improving the resampling method and reduce the computation quantity of distributed unscented particle filter（DUPF）.First,the intelligent optimized resampling method basing on artificial fish-swarm algorithm was used to overcome degeneracy and losing particle density ***,to overcome the higher computational complexity problem,the marginalized distribution simplified method was used in sampling particles and calculating weights of *** to DUPF FastSLAM,the AFSO-DUPF FastSLAM can maintain the diversity of particle and avoid inconsistency for long time *** simulation experiment results demonstrate that the improved FastSLAM system has higher estimation accuracy and reduce the computational complexity.

关键词： Distributed FastSLAM Unscented Particle Filter Artificial Fish-Swarm Resampling

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A GPRFNN-based control system for Wastewater Treatment Process 35

A GPRFNN-based Control System for Wastewater Treatment Proce...

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第35届中国控制会议

作者： HAN Gaitang HAN Honggui QIAO Junfei College of Electronic Information & Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

As a nonlinear and time-varying complex dynamic system, wastewater treatment process(WWTP) is difficult to be controlled. In this paper, to control the dissolved oxygen(DO) concentration in a WWTP, a growing and pruning recurrent fuzzy neural network(GPRFNN)-based control system is proposed which contains RFNN controllers and RFNN identifier. The identifier is used to model the WWTP with an adaptive algorithm to afford model information for the controllers, while the controllers are designed to adjust the control variables to make the WWTP run smoothly. Furthermore, the structure of the RFNN is self-organized to keep the output steady in structural adjustment phase, which is also theoretically proved. Finally, the control performance of the proposed system is shown by simulation results.

关键词： Wastewater Treatment Process Recurrent Fuzzy Neural Networks Dissolved Oxygen Self-organizing Mechanism

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Prediction of PM2.5 based on Elman neural network with chaos theory 35

Prediction of PM2.5 based on Elman neural network with chaos...

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第35届中国控制会议

作者： HU Zhiqiang LI Wenjing QIAO Junfei College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

PM2.5 is difficult to accurately forecast due to the influence of multiple meteorological and pollutant variables in the complex nonlinear dynamic atmosphere *** this paper,an Elman neural network prediction method based on chaos theory is put forward for the ***,the chaotic characteristics of the concentration of the PM2.5 are analyzed and verified from the correlation dimension,the maximum Lyapunov exponent and the Kolmogorov ***,phase space reconstruction technique of chaotic theory is adopted to reconstruct the phase space of PM2.5 time *** reconstructed phase space and the future concentration of PM2.5 are taken as the input and output of the Elman neural network with chaos theory(Elman-chaos) *** numerical and experimental analyses show that this method is proportionally superior to that without considering the chaos characteristics and other *** Elman-chaos prediction model has better prediction performance and application value.

关键词： PM2.5 Chaos Phase space reconstruction Elman neural network Prediction

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Progress of the TianQin project

arXiv

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arXiv 2025年

作者： Luo, Jun Bai, Shaojun Bai, Yan-Zheng Cai, Lin Dang, Hao Dong, Qijia Duan, Hui-Zong Du, Yuanbo Fan, Lei Fu, Xinju Gao, Yong Gou, Xingyu Gu, Defeng Guo, Changlei Hong, Wei Hu, Bin Hu, Heran Hu, Ming Hu, Yi-Ming Huang, Fa Peng Ji, Xin Jiang, Yuan-Ze Li, En-Kun Li, Hongyin Li, Ming Li, Ming Li, Yong Li, Zhu Li, Zizheng Lian, JunXiang Liang, Yu-Rong Lin, Xudong Liu, Jianping Liu, Lin-Xia Liu, Kui Liu, Li Liu, Minghe Liu, Qi Liu, Yan-Chong Liu, Yue Luo, Peng-Shun Luo, Yingxin Ma, Yi-Qiu Ma, Yun Meng, Yunhe Milyukov, Vadim Peng, Jian-Guo Postnov, Konstantin Qu, Shao-Bo Shan, Tilei Shao, Cheng-Gang Shi, Changfu Song, Pei-Yi Song, Yunfei Su, Wei Tan, Ding Yin Tan, Shuping Tan, Yu-Jie Tan, Wenhai Tu, Liangcheng Wang, Cheng-Rui Wang, Guoyong Wang, Lijiao Wang, Pan-Pan Wang, Shun Wang, Xiaoyong Wang, Xudong Wang, Yan Wei, Ran Wu, Shu-Chao Xu, Jie Xu, Zhi-Lin Xue, Chao Yan, Hao Yan, Yong Yang, Changpeng Yang, Shanqing Yeh, Hsien-Chi Yin, Hang Tong, Yelong Yu, Jian-Bo Yuan, Wen-Hao Zhang, Bu-Tian Zhang, Dexuan Zhang, Jian-Dong Zhang, Jie Zhang, Lihua Zhang, Xuefeng Zhao, Guoying Zhao, Liqian Zhao, Xin Zhou, An-Nan Zhou, Hao Zhou, Peng Zhou, Yupeng Zhou, Ze-Bing Zhu, Fan Zhu, Liang-Gui Zhu, Lin Zou, Kui Mei, Jianwei MOE Key Laboratory of TianQin Mission TianQin Research Center for Gravitational Physics School of Physics and Astronomy Frontiers Science Center for TianQin Gravitational Wave Research Center of CNSA Sun Yat-sen University Zhuhai Campus Zhuhai519082 China National Gravitation Laboratory MOE Key Laboratory of Fundamental Physical Quantities Measurement School of Physics Huazhong University of Science and Technology Wuhan430074 China DFH Satellite Co. Ltd. Beijing100094 China Beijing Institute of Space Mechanics & Electricity Beijing100076 China National Key Laboratory of Spacecraft Thermal Control of Institute of Spacecraft System Engineering Beijing100094 China Space Star Technology CO. LTD. Beijing100095 China Beijing Institute of Control Engineering Beijing100094 China School of Artificial Intelligence Sun Yat-sen University Zhuhai Campus Zhuhai519082 China Shanxi Xi’an710199 China Sternberg Astronomical Institute M.V. Lomonosov Moscow State University Moscow119234 Russia Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China

TianQin is a future space-based gravitational wave observatory targeting the frequency window of 10−4 Hz ∼ 1 Hz. A large variety of gravitational wave sources are expected in this frequency band, including the merger of massive black hole binaries, the inspiral of extreme/intermediate mass ratio systems, stellar-mass black hole binaries, Galactic compact binaries, and so on. TianQin will consist of three Earth orbiting satellites on nearly identical orbits with orbital radii of about 105 km. The satellites will form a normal triangle constellation whose plane is nearly perpendicular to the ecliptic plane. The TianQin project has been progressing smoothly following the "0123" technology roadmap. In step "0", the TianQin laser ranging station has been constructed and it has successfully ranged to all the five retro-reflectors on the Moon. In step "1", the drag-free control technology has been tested and demonstrated using the TianQin-1 satellite. In step "2", the inter-satellite laser interferometry technology will be tested using the pair of TianQin-2 satellites. The TianQin-2 mission has been officially approved and the satellites will be launched around 2026. In step "3", i.e., the TianQin-3 mission, three identical satellites will be launched around 2035 to form the space-based gravitational wave detector, TianQin, and to start gravitational wave detection in space. © 2025, CC BY.

关键词： Laser interferometry

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