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Neural-LAFC: A Neural Learning Adaptive Flight controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels

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Modified Hough Transform Based Registration Method for Heavy-haul Railway Rail Profile with Intensive Environmental Noise

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： An, Yuntong Cao, Yuan Sun, Yongkui Su, Shuai Wang, Feng Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation Control System School of Automation and Intelligent Beijing100044 China Beijing Jiaotong University Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China

In heavy-haul railway inspections, accurate rail profile registration is essential for assessing wear and deformation of tracks. In this process, identifying the rail waist arc as key segments and determining the center of the arc as feature points are crucial steps for rough rail profile registration, often affected by noise from sensors, surface contaminants, and environmental factors. To address these challenges, a profile registration method is proposed, with the Modified Hough Transform (MHT) as a core component. The method first segments key profile sections using curvature thresholds to identify arc segments. For each point in these segments, MHT constructs circles with fixed radius and calculates their intersection points. A distance matrix based on Euclidean distances between intersection points is generated. By sorting and normalizing these distances, the method identifies local density variations and calculates density coefficients to find the circle center, without manual thresholding. Comparative experiments on simulated and field data show that the proposed method achieves high accuracy and robustness in noisy environments. The dual validation confirms its reliability, making this method effective for rail profile registration in heavy-haul railway inspections. © 1963-2012 IEEE.

关键词： Hough transforms

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Revisiting the interplay between Comammox and Anammox: cooperative or competitive?

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Journal of Water Process engineering 2025年 75卷

作者： Bian, Yihao Fu, Kunming He, Xun Li, Xiaodan Wang, Xinlin Zhang, Yongji State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai 200092 China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092 China Key Laboratory of Urban Storm Water System and Water Environment Ministry of Education Beijing University of Civil Engineering and Architecture Beijing 100044 China

Complete ammonia oxidation (Comammox) has challenged the traditional two-step nitrification paradigm and reshaped the understanding of nitrogen removal in wastewater treatment. Anaerobic ammonia oxidation (Anammox) technology is considered as a suitable process for future wastewater treatment. However, the limited availability of substrates for Anammox has consistently hindered its broader application. The Comammox process has often been neglected in previous studies of Anammox. However, as far as the current study is concerned, Comammox may contribute to the advancement of wastewater treatment in the future with its wide distribution, strong environmental adaptability and low greenhouse-gas emissions. Recent studies have shown that Comammox may have the ability of nitrite leakage during ammonia oxidation, which provides a new pathway for substrate acquisition for the Anammox process. In this study, the relationship between Comammox and Anammox was elaborated based on their functions by comparing the distribution of both, as well as the similarity and specificity of the effects of different environmental factors on them. It was noted that the synergistic effects of Comammox and Anammox should be further explored. A possible strategy to achieve a fast nitrite supply by Comammox is proposed and the optimization of kinetic parameters is suggested. © 2025 Elsevier Ltd

关键词： Anammox Comammox N2O Nitrification Nitrite

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Optimal design and techno-economic analysis of a desert off-grid photovoltaic-to-hydrogen system integrated with pipeline networks

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Energy Conversion and Management 2025年 336卷

作者： Xu, Jiaxin Lin, Jin Li, Jiarong Lin, Ruixiao Pan, Guangsheng Department of Electrical Engineering Tsinghua University Beijing China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China Tsinghua-Sichuan Energy Internet Research Institute Chengdu China Harvard John A Paulson School of Engineering and Applied Sciences Harvard University Cambridge United States School of Electrical Engineering Southeast University Nanjing China

Addressing the challenge of harnessing remote solar resources for sustainable hydrogen production, this study presents a scalable off-grid photovoltaic-to-hydrogen (OgPVtH) system. We propose a bottom-up design methodology for the OgPVtH system, capturing the interconnections between land, water, and energy at micro and macro levels. At the micro level, we propose and consider the dynamic water-power-hydrogen characteristics of electrolyzers in a precise capacity allocation optimization model. At the macro level, we consider pipeline dynamic operating pressure constraints and establish a robust method for generating water-hydrogen pipeline network topologies. We conduct a real case study in the Hobq Desert. It reveals a levelized cost of hydrogen (LCOH) of 2.59 $/kg for the proposed OgPVtH system, indicating a 3.0 % lower cost compared to coal-based hydrogen production with carbon capture and storage (CCS) and 25 %-50 % lower cost compared to bioenergy to hydrogen, which demonstrates the system's economic competitiveness. The precise modeling of water-power-hydrogen characteristics and topologies can reduce LCOH by 0.35 $/kg and 0.01 $/kg, respectively. Sensitivity analysis highlights the trade-offs between investment in transmission and storage due to operational volatility, with an optimal hydrogen flow rate volatility of 80 % minimizing the total LCOH. © 2025 Elsevier Ltd

关键词： Hydro energy

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Differential-Trust-Mechanism Based Trade-off Method Between Privacy and Accuracy in Recommender systems

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5054-5068页

作者： Xu, Guangquan Feng, Shicheng Xi, Hao Yan, Qingyang Li, Wenshan Wang, Cong Wang, Wei Liu, Shaoying Tian, Zhihong Zheng, Xi Qingdao Huanghai University School of Big Data Qingdao China Tianjin University College of Intelligence and Computing Tianjin300350 China KLISS and School of Software Beijing100084 China Sichuan University School of Cyber Science and Engineering Chengdu610207 China Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China East China Normal University Shanghai200062 China Hiroshima University School of Informatics and Data Science Higashihiroshima739-8511 Japan Guangzhou University Cyberspace Institute of Advanced Technology Guangdong Key Laboratory of Industrial Control System Security Huangpu Research School of Guangzhou University China Macquarie University School of Computing SydneyNSW2109 Australia

In the era where Web3.0 values data security and privacy, adopting groundbreaking methods to enhance privacy in recommender systems is crucial. Recommender systems need to balance privacy and accuracy, while also having the ability to overcome cold start problems. The Differential Trust Mechanism (DTM) introduced in this paper is such an approach. The DTM provides a unique use of Gaussian distributions in modeling trust relationships within data, offering a novel way to balance recommendation accuracy with user privacy. This mechanism innovatively applies differential privacy principles, using Gaussian noise addition to protect individual user data from inference attacks, while maintaining the integrity and utility of the overall dataset. Unlike traditional anonymization techniques that often compromise data utility or vulnerability to reverse engineering, DTM provides a robust solution by dynamically adjusting privacy levels based on the trustworthiness of data requests. By combining DTM with existing mainstream recommendation algorithms, the prediction accuracy of MAE and RMSE increases by at least 6.60% and 2.69%, respectively. This dual benefit positions DTM as a significant advancement in secure data processing, especially relevant for online businesses and platforms where personalized recommendations are crucial yet privacy concerns are paramount. © 2005-2012 IEEE.

关键词： Sensitive data

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PreAdaptFWI: Pretrained-Based Adaptive Residual Learning for Full-Waveform Inversion Without Dataset Dependency

arXiv

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arXiv 2025年

作者： Dong, Xintong Yuan, Zhengyi Lin, Jun Dong, Shiqi Tong, Xunqian Li, Yue College of Instrumentation and Electrical Engineering Jilin University Changchun130026 China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Northeast Electric Power University Jilin132012 China College of Communication Engineering Jilin University Changchun130012 China

Full-waveform inversion (FWI) is a method that utilizes seismic data to invert the physical parameters of subsurface media by minimizing the difference between simulated and observed waveforms. Due to its ill-posed nature, FWI is susceptible to getting trapped in local minima. Consequently, various research efforts have attempted to combine neural networks with FWI to stabilize the inversion process. This study presents a simple yet effective training framework that is independent of dataset reliance and requires only moderate pre-training on a simple initial model to stabilize network outputs. During the transfer learning phase, the conventional FWI gradients will simultaneously update both the neural network and the proposed adaptive residual learning module, which learns the residual mapping of large-scale distribution features in the network’s output, rather than directly fitting the target mapping. Through this synergistic training paradigm, the proposed algorithm effectively infers the physically-informed prior knowledge into a global representation of stratigraphic distribution, as well as capturing subtle variations in inter-layer velocities within local details, thereby escaping local optima. Evaluating the method on two benchmark models under various conditions, including absent low-frequency data, noise interference, and differing initial models, along with corresponding ablation experiments, consistently demonstrates the superiority of the proposed approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Stratigraphy

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Research on frequency modulation of thermal power units combined with compressed air energy storage based on model predictive control

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International Journal of Electrical Power and Energy systems 2025年 168卷

作者： Lv, You Sun, Hao Wu, Bin Shi, Yijun Fang, Fang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Changping District Beijing102206 China School of Control and Computer Engineering North China Electric Power University Changping District Beijing102206 China

Amidst China's pursuit of carbon peaking and neutrality targets, there is a pressing need to establish a novel power system that primarily relies on renewable energy sources (RES). To tackle the challenges this transition poses to the existing power grid, it is imperative to fortify the power system's frequency modulation capabilities, which in turn calls for the exploration of diverse energy storage solutions. This research introduces, simulates, and evaluates an innovative charge–discharge control methodology designed to augment the frequency modulation capabilities of the thermal power unit (TPU) through the integration of the compressed air energy storage (CAES) system. Firstly, by considering the dynamic characteristics and operational mechanism, fundamental transfer function models for TPU and the CAES system are established;based these models, the frequency modulation model of a two-area power grid incorporating TPU and CAES is presented. Subsequently, a power adaptive allocation strategy is formulated with nonlinear signal decomposition techniques, enabling adaptive power distribution between TPUs and CAES. Furthermore, a control strategy utilizing model predictive control (MPC) is proposed, taking into account the state of charge (SOC) of CAES, to refine the energy charge and discharge process. The effectiveness is tested under two scenarios: step disturbance and continuous disturbance. Compared to TPU-only frequency modulation, the presented strategy achieves remarkable outcomes: a 21.9 % reduction in maximum frequency deviation following step disturbances, a 52.2 % decrease in steady-state frequency deviation, and a 37.5 % mitigation of TPU output power fluctuations under continuous disturbances. The results underscore the significant potential of the proposed strategy in alleviating the frequency modulation burden on TPUs, thereby contributing to their secure and stable operation within the evolving power system landscape. © 2025 The Author(s)

关键词： Compressed air energy storage

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Accurate decomposition of complex multi-component nonstationary signals of rotating machinery: A novel polynomial chirp mode decomposition approach

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Fu, Bo Wu, Rongchuan Quan, Yi Lic, Chaoshun Zhao, Xilin School of Electrical and Electronic Engineering Hubei University of Technology Wuhan430068 China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology Wuhan430068 China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China

In complex operating environments, the monitoring signals of rotating machinery often exhibit significant nonlinearity and non-stationarity, which creates major challenges for fault diagnosis. Although adaptive chirp mode decomposition (ACMD) offers high time–frequency resolution, its performance deteriorates with inaccurate initial instantaneous frequency (IF) estimation and shows limitations when processing signals with crossing IFs. To address these issues, this paper proposes a novel polynomial chirp mode decomposition (PCMD) method to enhance decomposition accuracy for complex multi-component signals. Firstly, we propose an adaptive IF optimization scheme (APIFO) based on the polynomial chirplet transform (PCT), which adaptively determines the fitting order of PCT in accordance with the error-adjusted R-Squared value to achieve accurate estimation of the IF. Secondly, based on demodulation techniques, we introduce an instantaneous amplitude (IA) chirp tracking filter to reconstruct the signal modes and extract the IA using the IF provided by APIFO. Finally, we propose an IA correction strategy for signals with crossing IFs. This strategy first classifies the signal modes by the absolute value of the second derivative of IA and then corrects the modes of different categories through weighted fitting or LSTM neural network methods. Simulation and experimental results demonstrate that the PCMD method provides superior IF estimation and accurate mode decomposition performance compared with classical techniques in rotating machinery fault diagnosis applications. © 2025

关键词： Empirical mode decomposition

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One-stone-two-birds: over 26% efficiency in perovskite solar cells via synergistic crystallization & interface regulation

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Energy and Environmental Science 2025年

作者： Jiao, Boxin Tan, Liguo Ye, Yiran Ren, Ningyu Li, Minghao Li, Hang Li, Xiaoyi Yi, Chenyi State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Center of Materials Science and Optoelectronics Engineering College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Institute of Carbon Neutrality Tsinghua University Beijing100084 China

Organic-inorganic hybrid perovskites have emerged as promising photovoltaic materials due to their excellent photoelectronic properties and low-cost fabrication techniques. However, the performance and stability of perovskite solar cells (PSCs) are compromised by the random orientation of optically active phase crystals and bulk/interface defects. In this paper, we developed a multifunctional organic material, parabanic acid, to regulate the crystallization and realize full-range defect passivation integrated passivation of defects in perovskites. Attributed to the synergistic effect of functional groups, perovskite films with concentrated out-of-plane spatial orientation were formed. In addition, the introduction of an interface passivation layer based on parabanic acid achieved integrated passivation of bulk and interface defects in perovskite solar cells. The resulting PSCs achieved a power conversion efficiency of 26.03% (certified 25.51%) with excellent environmental stability. Notably, under standard measurement conditions (ISOS-L-1I), the maximum power point output maintained 96.3% of its initial efficiency over 2000 hours. The synergistic regulation of crystal orientation and integrated passivation of defects provide a new approach to promote the development of perovskite solar cells. © 2025 The Royal Society of Chemistry.

关键词： Organic-inorganic materials

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A constant quasi-zero stiffness isolator with tension springs to isolate vibrations with ultralow frequency

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International Journal of Non-Linear Mechanics 2025年 175卷

作者： Zhao, Feng Ji, J.C. Cao, Shuqian Zheng, Jingyang Luo, Quantian Department of Mechanics Tianjin University Tianjin300354 China Tianjin Key Laboratory of Nonlinear Dynamics and Control National Key Laboratory of Vehicle Power System Tianjin300354 China College of Mechanical and Electrical Engineering Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment Zhengzhou University of Light Industry Zhengzhou450002 China School of Mechanical and Mechatronic Engineering University of Technology Sydney NSW2007 Australia College of Vehicle and Traffic Engineering Henan University of Science and Technology Luoyang471003 China

Many types of quasi-zero stiffness (QZS) isolators have been developed to isolate vibrations with low frequencies. However, isolating vibrations with ultralow frequency as low as 1 Hz is still a great challenge even in laboratory tests due to the high damping of QZS prototypes. To address this issue, a novel isolator with intrinsically light damping is proposed by configurating tension springs and oblique bars. The linear or nonlinear negative stiffness generated by the horizontal tension springs and oblique bars counteracts the linear positive stiffness of the vertical tension springs to obtain the QZS-related features including nonlinear QZS, constant positive or negative dynamic stiffness, constant QZS, and constant zero stiffness. Two QZS conditions are derived and the influence of parameters on QZS is thoroughly studied. The proposed isolator with tension springs has obvious differences from the previous isolator with compression springs in terms of QZS conditions, as well as force and stiffness expressions. Then, the displacement transmissibility is calculated by using the increment harmonic balance method and the continuous arc-length algorithm, which is verified by the classical harmonic balance method. These methods have the same prediction result. Finally, a prototype is fabricated and tested. The smoother force curves with constant QZS and the higher transmissibility amplitude can be obtained in tests compared to the previous isolator with compression springs under the same configuration parameters, which verifies the theoretical formulations of the proposed isolator with light damping. The prototype is further improved by replacing linear bearings with sliders to reduce the frictional effects. As a result, vibrations with ultralow frequencies lower than 1 Hz are successfully isolated. The proposed isolator has a wider frequency band and lower transmissibility than the previous isolator with compression springs. This study offers an effective method of de

关键词： Damping

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