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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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Prediction of NO_(x)concentration using modular long short-term memory neural network for municipal solid waste incineration

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Chinese Journal of Chemical Engineering 2023年第4期56卷 46-57页

作者： Haoshan Duan Xi Meng Jian Tang Junfei Qiao Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing 100124China

Air pollution control poses a major problem in the implementation of municipal solid waste incineration(MSWI).Accurate prediction of nitrogen oxides(NO_(x))concentration plays an important role in efficient NO_(x)emission *** this study,a modular long short-term memory(M-LSTM)network is developed to design an efficient prediction model for NO_(x)***,the fuzzy C means(FCM)algorithm is utilized to divide the task into several sub-tasks,aiming to realize the divide-and-conquer ability for complex ***,long short-term memory(LSTM)neural networks are applied to tackle corresponding sub-tasks,which can improve the prediction accuracy of the ***,a cooperative decision strategy is designed to guarantee the generalization performance during the testing or application ***,after being evaluated by a benchmark simulation,the proposed method is applied to a real MSWI *** the experimental results demonstrate the considerable prediction ability of the M-LSTM network.

关键词： Municipal solid waste incineration NO_(x)concentration prediction Modular neural network Model

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Targeting 5-HT to Alleviate Dose-Limiting Neurotoxicity in Nab-Paclitaxel-Based Chemotherapy

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Neuroscience bulletin 2025年 2025 May 14页

作者： Shuangyue Pan Yu Cai Ronghui Liu Shuting Jiang Hongyang Zhao Jiahong Jiang Zhen Lin Qian Liu Hongrui Lu Shuhui Liang Weijiao Fan Xiaochen Chen Yejing Wu Fangqian Wang Zheling Chen Ronggui Hu Liu Yang Second Clinical Medical College Zhejiang Chinese Medical University Hangzhou 310000 China. Cancer Center Department of Medical Oncology Zhejiang Provincial People's Hospital Affiliated People's Hospital Hangzhou Medical College Hangzhou 310014 China. Department of Orthopedic Surgery Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou 310000 China. wfqzju@***. Cancer Center Department of Medical Oncology Zhejiang Provincial People's Hospital Affiliated People's Hospital Hangzhou Medical College Hangzhou 310014 China. chenzheling@***. Department of Colorectal Surgery and Oncology (Key Laboratory of Cancer Prevention and Intervention China National Ministry of Education) The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou 310000 China. coryhu00@***. Center for Medical Research and Innovation in Digestive System Tumors Ministry of Education Hangzhou 310000 China. coryhu00@***. Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-machine Integration State Key Laboratory of Brain-machine Intelligence Zhejiang University Hangzhou 311121 China. coryhu00@***. Cancer Center Department of Medical Oncology Zhejiang Provincial People's Hospital Affiliated People's Hospital Hangzhou Medical College Hangzhou 310014 China. yangliu@***. Zhejiang Provincial Clinical Research Center for Head and Neck Cancer Zhejiang Key Laboratory of Precision Medicine Research on Head and Neck Cancer Zhejiang Province Key Disciplines in Traditional Chinese Medicine-Integrated Traditional Chinese and Western Medicine Clinical Oncology Hangzhou 310014 China. yangliu@***.

Chemotherapy-induced peripheral neurotoxicity (CIPN) is a severe dose-limiting adverse event of chemotherapy. Presently, the mechanism underlying the induction of CIPN remains unclear, and no effective treatment is available. In this study, through metabolomics analyses, we found that nab-paclitaxel therapy markedly increased serum serotonin [5-hydroxtryptamine (5-HT)] levels in both cancer patients and mice compared to the respective controls. Furthermore, nab-paclitaxel-treated enterochromaffin (EC) cells showed increased 5-HT synthesis, and serotonin-treated Schwann cells showed damage, as indicated by the activation of CREB3L3/MMP3/FAS signaling. Venlafaxine, an inhibitor of serotonin and norepinephrine reuptake, was found to protect against nerve injury by suppressing the activation of CREB3L3/MMP3/FAS signaling in Schwann cells. Remarkably, venlafaxine was found to significantly alleviate nab-paclitaxel-induced CIPN in patients without affecting the clinical efficacy of chemotherapy. In summary, our study reveals that EC cell-derived 5-HT plays a critical role in nab-paclitaxel-related neurotoxic lesions, and venlafaxine co-administration represents a novel approach to treating chronic cumulative neurotoxicity commonly reported in nab-paclitaxel-based chemotherapy.

关键词： Chemotherapy-induced peripheral neurotoxicity Nab-paclitaxel Serotonin Venlafaxine

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Ni-doped ZrSe2 monolayer as a promising NO2 and O3 gas sensor in ring main unit: A first-principles study

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Molecular Physics 2025年

作者： Jiang, Shaoming Wu, Hailong Li, Fu Cui, Hao College of Physics and Electronic Information Engineering Neijiang Normal University Neijiang China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Neijiang Normal University Neijiang China College of Artificial Intelligence Southwest University Chongqing China

This study utilising first-principles theory investigates the potential of Ni-doped ZrSe2 (Ni-ZrSe2) monolayer as a potential sensing material upon NO2 and O3 gases for evaluating the operational status of ring main units (RMUs). The adsorption characteristics and electronic properties of Ni-ZrSe2 monolayers upon two gases are analyzed, revealing the underlying resistive, magnetic, and Schottky gas sensing mechanisms. Our findings indicate that Ni-ZrSe2 monolayer exhibits chemisorption upon NO2 and O3 molecules with adsorption energies of −1.35 and −1.69 eV, respectively. Both molecules behave electron-accepting property with charge transfer of −0.144 and −0.160 e, leading to metallic behaviour for the monolayer. The monolayer-based resistive sensor is capable of detecting both gases, while the magnetic sensor can specifically detect O3. Furthermore, the Ni@Ni-ZrSe2-based Schottky gas sensor reveals the favourable selectivity and sensitivity towards NO2 and O3. These results highlight the significant potential of Ni-ZrSe2 monolayers for typical gas detection in RMUs, offering a promising approach for monitoring electrical equipment using ZrSe2-based gas sensors. This research contributes to the development of more efficient and reliable gas sensing technologies for environmental and industrial applications. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Gas detectors

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Development of a novel autonomous lower extremity exoskeleton robot for walking assistance

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Frontiers of Information Technology & Electronic Engineering 2019年第3期20卷 318-329页

作者： Yong HE Nan LI Chao WANG Lin-qing XIA Xu YONG Xin-yu WU Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical Engineering and Intelligent Systems the University of Electro-Communications

Today, exoskeletons are widely applied to provide walking assistance for patients with lower limb motor incapacity. Most existing exoskeletons are under-actuated, resulting in a series of problems, e.g., interference and unnatural gait during walking. In this study, we propose a novel intelligent autonomous lower extremity exoskeleton(Auto-LEE), aiming at improving the user experience of wearable walking aids and extending their application *** traditional exoskeletons, Auto-LEE has 10 degrees of freedom, and all the joints are actuated independently by direct current motors, which allows the robot to maintain balance in aiding walking without extra *** new exoskeleton is designed and developed with a modular structure concept and multi-modal human-robot interfaces are considered in the control system. To validate the ability of self-balancing bipedal walking, three general algorithms for generating walking patterns are researched, and a preliminary experiment is implemented.

关键词： Lower-limb Exoskeleton Self-balancing Bipedal walking Modular design

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A New Robust Adaptive Neural Network Backstepping control for Single machine Infinite Power system With TCSC

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IEEE/CAA Journal of Automatica Sinica 2020年第1期7卷 48-56页

作者： Yanhong Luo Shengnan Zhao Dongsheng Yang Huaguang Zhang A new robust adaptive neural network backstepping control for single machine infinite power system with TCSC Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110004 School of Information Science and Engineering Northeastern UniversityShenyang 110004China

For a single machine infinite power system with thyristor controlled series compensation(TCSC) device, which is affected by system model uncertainties, nonlinear time-delays and external unknown disturbances, we present a robust adaptive backstepping control scheme based on the radial basis function neural network(RBFNN). The RBFNN is introduced to approximate the complex nonlinear function involving uncertainties and external unknown disturbances, and meanwhile a new robust term is constructed to further estimate the system residual error,which removes the requirement of knowing the upper bound of the disturbances and uncertainty terms. The stability analysis of the power system is presented based on the Lyapunov function,which can guarantee the uniform ultimate boundedness(UUB) of all parameters and states of the whole closed-loop system. A comparison is made between the RBFNN-based robust adaptive control and the general backstepping control in the simulation part to verify the effectiveness of the proposed control scheme.

关键词： Backstepping control radial basis function neural network(RBFNN) robust adaptive control thyristor controlled series compensation(TCSC) uniform ultimate boundedness(UUB)

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A Survey on Distributed Network Localization from a Graph Laplacian Perspective

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Journal of systems Science & Complexity 2024年第1期37卷 273-293页

作者： HAN Zhimin LIN Zhiyun FU Minyue Artificial Intelligence Institute School of AutomationHangzhou Dianzi UniversityHangzhou 310018China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyShenzhen 518055China Peng Cheng Laboratory Shenzhen 518000China

Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate position information for all nodes in the *** localization focuses on the challenge of determining the positions of nodes within a network,relying on the known positions of anchor nodes and internode relative *** the past few decades,distributed network localization has garnered significant attention from *** paper aims to provide a review of main results and advancements in the field of distributed network localization,with a particular focus on the perspective of graph *** to its favorable characteristics,graph Laplacian unifies various network localization,even when dealing with diverse types of internode relative measurements,into a unified protocol framework,which can be constructed by a linear method and ensure the global convergence.

关键词： Distributed network localization graph Laplaian sensor network

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