检索结果-南通市图书馆

Stability and Stabilization of Sampled-Data Based LFC for Power systems:A Data-Driven Method

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第1期 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of automation China University of Geosciences the Hubei key laboratory of Advanced control and Intelligent automation for Complex systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词：

Physical Layer Security Scheme With AoI-Awareness for Industrial IoT Based on Covert Communications

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第1期 276-278页

作者： Yaping Li Zhi-Xin Liu Jia-Wei Su Ya-Zhou Yuan the key laboratory of Industrial Computer control Engineering of Hebei Province Yanshan University

Dear Editor,Industrial Internet of things(IIoT) is a typical application of cyberphysical system(CPS). In the IIoT, wireless communication is an inevitable trend to replace the deployment-limited wired transmission for cases with large-scale and mobile devices. However, wireless communication gives rise to critical issues related to physical security, such as malicious detections and attacks [1].

关键词：

Targets capture by distributed active swarms via bio-inspired reinforcement learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace control Technology Institute Shanghai key laboratory of Aerospace Intelligent control Technology College of automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

Decentralized fault diagnosis of discrete-event systems with unreliable sensors using linear temporal logic

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2025年第1期 322-341页

作者： Weijie DONG Shaoyuan LI Xiang YIN key laboratory of system control and Information Processing Ministry of EducationDepartment of Automation Shanghai Jiao Tong University

In this paper,we investigate a decentralized diagnosis problem of a discrete-evnt system(DES) subject to unreliable sensors,where the sensor observations of local diagnosers may be non-deterministic as a result of possible *** studies on decentralized robust diagnosis can only deal with different types of sensor failures separately,e.g.,all sensors suffer from the same type of sensor failures such as intermittent sensor failures or permanent sensor ***,since sensors of different local diagnosers may face different external environments and have different internal characteristics,sensors corresponding to different local diagnosers may also have their own fault *** this paper,we propose a flexible framework of decentralized diagnosis for DES subject to unreliable sensors such that sensors of different local diagnosers are permitted to have different types of sensor *** this end,we extend the existing decentralized diagnosis framework to the case where there exist common sensors broadcasting their observations to all local *** apply linear temporal logic(LTL) to constrain infinite behaviors of private sensors of local diagnosers and common ***,a new notion of φ-codiagnosability is proposed as the necessary and sufficient condition for the existence of a decentralized diagnoser that works correctly under sensors,satisfying LTL-based sensor ***,we provide an effective approach to verify the φ-codiagnosability.

关键词：

An algorithm for trajectory prediction of flight plan based on relative motion between positions

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Information Technology & Electronic Engineering 2018年第7期19卷 905-916页

作者： Yi LIN Jian-wei ZHANG Hong LIU National key laboratory of Fundamental Science on Synthetic Vision Sichuan University National key laboratory of air traffic control automation system Technology Sichuan University

Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed(constant, acceleration, or deceleration), yaw(left, right, or straight), and pitch(climb, descent, or cruise) using a hidden Markov model(HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models(GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.

关键词： Velocity vector Hidden Markov model Gaussian mixture model Machine learning Plan path prediction Relative motion between positions(RMBP)

维普期刊数据库

Leader-follower: Human-centered intention-guided controller for novel SuperLimb with application to load-carrying scenarios

在线全文

学校读者我要写书评

暂无评论

Science China Technological Sciences 2025年第1期 325-338页

作者： Qinghua ZHANG Xianglong LI Hongwei JING Kerui SUN Yuancheng LI Sikai ZHAO Lele LI Haotian JU Ziqi WANG Rui WU Tianjiao ZHENG Jie ZHAO Yanhe ZHU The State key laboratory of Robotics and system Harbin Institute of Technology The Learning Algorithms and systems laboratory School of Engineeringécole Polytechnique Fédérale de Lausanne

Supernumerary robotic arms(SuperLimb) are a new type of wearable robot that works closely with humans as a third hand to augment human operation capability. Accurate conveyance of wearers' intentions, allocation of roles, and humancentered interaction considerations are the key points in the process of human–SuperLimb collaboration. This paper proposes a human-centered intention-guided leader–follower controller that relies on the dynamic modeling of SuperLimb with application to load-carrying scenarios. The proposed leader–follower controller takes the human as the leader and the SuperLimb as the follower, achieving effective information communication, autonomous coordination, and good force compliance between SuperLimb, humans, and the environment under human safety assurance. First, the human–SuperLimb dynamic system is modeled to achieve force interaction with the environment and wearer. Second, to achieve the precise intention extraction of humans, pose data from five visual odometry sensors are fused to capture the human state, the generalized position, the velocity of hands, and the surface electromyography signals from two myoelectric bracelets sensors are processed to recognize the natural hand gestures during load-carrying scenarios by a designed Swin transformer network. Then, based on the real-time distance detection between human and mechanical limbs, the security assurance and force-compliant interaction of the human–SuperLimb system are realized. Finally, the human hand muscle intention recognition, human–robot safety strategy verification,and comparative load-carrying experiments with and without the proposed method are conducted on the SuperLimb *** showed that the task parameters are well estimated to produce more reasonable planning trajectories, and SuperLimb could well understand the wearer's intentions to switch different SuperLimb actions. The proposed sensor-based human–robot communication framework motivates future studies of o

关键词：

Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第9期20卷 2520-2537页

作者： Chonglin Su Taiqi Huang Meiyu Zhang Yanyu Zhang Yan Zeng Xingxing Chen Brain Science and Advanced Technology Institute Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of MedicineWuhan University of Science and TechnologyWuhanHubei ProvinceChina

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental *** the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and *** glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic *** interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive *** appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive *** with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor *** review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive *** emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive *** provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.

关键词： brain-derived neurotrophic factor calcium signaling glucocorticoid receptor glucocorticoid glutamate transmission hypothalamic-pituitary-adrenal axis long-term potentiation neurocognitive disorders neuroplasticity stress

维普期刊数据库

Low-cost and fluoride-free synthesis of MFI zeolite nanosheets with enhanced stability for benzene alkylation with ethanol

在线全文

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 458-468页

作者： Peng Zhu Cun Liu Yiren Yu Guoshu Gao Yumeng Zhao Xiongfu Zhang Guodong Liu Guohui Yang State key laboratory of Fine Chemicals School of Chemical Engineering Dalian University of Technology State key laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Zeolite nanosheets with a short b-axis thickness are highly desirable in lots of catalytic reactions due to their reduced diffusion resistance. Nevertheless, conventional synthesis methods usually require expensive structure-directing agents(SDAs), pricey raw materials, and eco-unfriendly fluorine-containing additives. Here, we contributed a cost-effective and fluoride-free synthesis method for synthesizing high-quality MFI zeolite nanosheets through a Silicalite-1(Sil-1) seed suspension and urea cooperative strategy, only with inexpensive colloidal silica as the Si source. Our approach was effective for synthesizing both Sil-1 and aluminum-containing ZSM-5 nanosheets. By optimizing key synthesis parameters,including seed aging time, seed quantity, and urea concentration, we achieved precise control over the crystal face aspect ratio and b-axis thickness. We also revealed a non-classical oriented nanosheet growth mechanism, where Sil-1 seeds induced the formation of quasi-ordered precursor particles, and the(010)crystal planes of these particles facilitated urea adsorption, thereby promoting c-axis-oriented *** obtained ZSM-5 nanosheets exhibited exceptional catalytic performance in the benzene alkylation with ethanol, maintaining stability for over 500 h, which is 5 times longer than traditional ZSM-5 catalysts. Furthermore, large-scale production of ZSM-5 nanosheets was successfully carried out in a 3 L highpressure autoclave, yielding samples consistent with those from laboratory-scale synthesis. This work marks a significant step forward in the sustainable and efficient production of MFI nanosheets using inexpensive and environmentally friendly raw materials, offering the broad applicability in catalysis.

关键词： MFI zeolite ZSM-5 Nanosheets Scale-up synthesis Aromatic alkylation

Identifying the dynamic behaviors in complete reconstruction of Co-based complex precatalysts during electrocatalytic oxygen evolution

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 226-233页

作者： Jingfang Zhang Danyang Wu Linke Cai Youluan Lu Fanpeng Cheng Lijuan Shi Qun Yi Yao Liu Yi Huang key laboratory of Green Chemical Engineering Process of Ministry of Education Engineering Research Center of Phosphorus Resources Development and Utilization of Ministry of Education Hubei Key Laboratory of Novel Reactor and Green Chemical Technology School of Chemical Engineering & Pharmacy Wuhan Institute of Technology key laboratory of Pesticide & Chemical Biology of Ministry of Education Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction of Ministry of Education College of Chemistry Central China Normal University College of Materials Science and Engineering Fuzhou University

Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction（OER）. Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under operating conditions of OER process. However, most of them undergo incomplete reconstruction with limited thickness of reconstruction layer, leading to low component utilization and arduous exploration of real catalytic mechanism. Herein, we identify the dynamic behaviors in complete reconstruction of Co-based complexes during OER. The hollow phytic acid（PA） cross-linked CoFe-based complex nanoboxes with porous nanowalls are designed because of their good electrolyte penetration and mass transport ability, in favor of the fast and complete reconstruction. A series of experiment characterizations demonstrate that the reconstruction process includes the fast substitution of PA by OH-to form Co（Fe）(OH)xand subsequent potential-driven oxidation to Co（Fe）OOH. The obtained CoFeOOH delivers a low overpotential of 290 mV at a current density of 10 mA cm-2and a long-term *** experiment results together with theory calculations reveal that the Fe incorporation can result in the electron rearrangement of reconstructed CoFeOOH and optimization of their electronic structure,accounting for the enhanced OER activity. The work provides new insights into complete reconstruction of metal-based complexes during OER and offers guidelines for rational design of high-performance electrocatalysts.

关键词： Complete reconstruction Co-based complex Precatalysts Oxygen evolution reaction