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22nd IFAC World Congress

作者： Janssen, Lars A.L. Besselink, Bart Fey, Rob H.B. van de Wouw, Nathan Dynamics and Control group Department of Mechanical Engineering Eindhoven University of Technology Netherlands Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Netherlands

ISBN: (纸本)9781713872344

Complex systems often involve interconnected subsystem models developed by multi-disciplinary teams. To simulate and control such systems, a reduced-order model of the interconnected system is required. In the scope of this paper, we pursue this goal by subsystem reduction to warrant modularity of the reduction approach. However, reducing subsystem models affects not only the subsystems accuracy, but also the interconnected model accuracy, making it difficult to predict a priori the accuracy impact of subsystem reduction. To address this challenge, we introduce a top-down approach using mathematical tools from robust performance analysis, enabling the translation of accuracy requirements from the interconnected model to the subsystem level. This enables independent subsystem reduction while ensuring the desired accuracy of the interconnected model. We demonstrate the effectiveness of our approach through a structural dynamics case study. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Complex systems control of interconnected systems Error bounds Model reduction Robust performance Top-down approach

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Analysis of HVAC sensor characteristics for operation and maintenance of the indoor environment: A case research on public building HVAC

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Building Simulation 2025年第5期18卷 1205-1228页

作者： Zhang, Boyan Wang, Jiaming Shangguan, Liuyang Rezgui, Yacine Ghoroghi, Ali Cao, Ximing Song, Chengzhe Ding, Menglin Zhao, Tianyi Institute of Building Energy Department of Civil Engineering Dalian University of Technology Dalian China School of Engineering Cardiff University Cardiff United Kingdom School of instrument and electronics North University of China Taiyuan China School of Information Science and Technology Fudan University Shanghai China Landscape Architecture Rhode Island School of Design Providence02903 United States Dalian Shenghe Automatic Control Technology Co. Ltd Dalian China

Sensors are a crucial component in heating, ventilation, and air conditioning (HVAC) control systems, and the quality of them plays an important role in control accuracy. In the research of fault detection and control optimization, improving sensor data quality has inspiring potential in application. It has been largely limited to the application of signal processing methods in research focus, whereas a detailed analysis of the characteristics of signals from various sensors of the HVAC system has not been conducted. Therefore, this study analyzes the time-frequency domain characteristics of control sensors within HVAC systems through integrating the structural design and control logic of such systems. Additionally, the research examines the correlations between control sensors in HVAC systems. Based on statistical principles and the energy-mass dynamic laws of the equipment, this paper defines first-class (I) correlated sensors and second-class (II) correlated sensors. To sum up, the main contribution of this paper is conducting a fundamental study on the characteristics of control sensors within HVAC systems, providing theoretical reference for future research on HVAC system fault diagnosis and control optimization. © Tsinghua University Press 2025.

关键词： HVAC

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Traditional Chinese Medicine Health Status Identification with Graph Attention Network 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Fu, Amin Ma, Jishun Wang, Chuansheng Zhou, Changen Li, Zuoyong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou350122 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The Traditional Chinese Medicine Health Status Identification plays an important role in TCM diagnosis and prescription recommendation. In this paper, we propose a method of Status Identification via Graph Attention Network, named SIGAT, which captures the complex medical correlation in the symptom-syndrome graph. More specifically, we construct a symptom-syndrome graph in that symptoms are taken as nodes and the edges are connected by syndromes. And we realize automatic induction of symptom to state element classification by using the attention mechanism and perceptron classifier. Finally, we conduct experiments by using hamming loss, coverage, 0/1 error, ranking loss, average precision, macro-F1 score, and micro-F1 score as evaluation metrics. The results demonstrate that the SIGAT model outperforms comparison algorithms on Traditional Chinese Medicine Prescription Dictionary dataset. The case study results suggest that the proposed method is a valuable way to identify the state element. The application of the graph attention network classification algorithm in TCM health status identification is of high precision and methodological feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Adaptability analysis on the measurement device of UACV special machinery unlocking force

Adaptability analysis on the measurement device of UACV spec...

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2023 International Conference on Mechatronic engineering and Artificial Intelligence, MEAI 2023

作者： Yang, Mo Cai, Zizhuo Lin, Jing Li, Jiahao Ren, Haiyue Liu, Qiang School of Mechanical Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing210094 China Department of Automatic Control Systems Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia

ISBN: (纸本)9781510674608

During the unlocking process of the rotating-bolt locking special machinery head, there is a significant resistance. The aim is to select a motor for unmanned aerial combat vehicle (UACV) mounted external power special machinery drives, taking the special machinery unlocking force as the research subject. Adaptive analysis is conducted on the patented structure of the special machinery unlocking force measurement device previously designed. A virtual prototype model is established using the dynamic simulation software ADAMS to apply driving, constraints, and simulation parameters based on the model's principles. Addressing the phenomenon of the detachment of the guide rod slider from the tested bolt carrier during the operation of the special machinery unlocking force measurement device, it is hypothesized that the detachment time is related to the stiffness of the spring and the velocity of the lead screw slider. Through multiple comparative simulations, the correctness of the hypothesis is proven. It is demonstrated that increasing the velocity of the lead screw slider can completely eliminate the detachment time, whereas increasing the stiffness of the spring, although reducing the detachment time, still results in secondary detachment. Consequently, the conclusion is drawn that increasing the velocity of the lead screw slider is the way to resolve the detachment issue of the guide rod slider from the tested bolt carrier in the experiment. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Multi-party secure communication using blockchain over 5G

Multi-party secure communication using blockchain over 5G

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Archana, K. Kareem, Z.H. Al-Farhani, Liwa H. Bagyalakshmi, K. Jenvi, Ignatia K. Majella Kumar, Ashok Department of Computer Engineering Pimpri Chinchwad College of Engineering and Research Maharashtra Pune India Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq System Analysis Control and Information Processing dep Academy of Engineering RUDN University Moscow Russia Sri Ranganathar Institute of Engineering and Technology Coimbatore India Mathematics Department Saveetha School of Engineering SIMATS Saveetha Nagar Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9781032669663

One of the most critical problems facing the blockchain technology industry right now is how to protect the privacy of users’ data on the blockchain in a way that is both effective and cheap. Based on the Pedersen commitment and the Schnorr protocol, this study comes up with a secure multi-party computing protocol (BPLSM). By making the structure of the protocol and doing formal proof calculations, it has been shown that the protocol can be used in the blockchain network to combine private messages for efficient signing while keeping people’s identities secret. Furthermore, by looking at the nature and security of the protocol, it is also possible to find that the BPLSM protocol on the blockchain has a low cost of computing and a high level of information secrecy. Furthermore, it was found that the BPLSM protocol takes less time to check than the current mainstream BLS signature in a simple multi-party transaction with a fixed number of participants. © 2024 The Author(s).

关键词： Blockchain

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Event-triggered leader-following formation control for multi-agent systems under communication faults: application to a fleet of unmanned aerial vehicles

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Journal of Systems engineering and Electronics 2021年第5期32卷 1014-1022页

作者： VAZQUEZ TREJO Juan Antonio GUENARD Adrien ADAM-MEDINA Manuel PONSART Jean-Christophe CIARLETTA Laurent ROTONDO Damiano THEILLIOL Didier Research Center for Automatic Control of Nancy University of LorraineNancy F-54000France Electronic Engineering Department National Institute of Technology of MexicoCuernavaca Morelos 62490Mexico Lorraine Research Laboratory in Computer Science and Its Applications University of LorraineNancy F-54000France University of Stavanger Department of Electrical and Computer EngineeringStavanger 4021Norway

The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems(MASs)under communication *** the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the *** matrix inequalities(LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization *** on the closed-loop system,an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy *** proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles(UAVs)under communication faults.A comparison between a state-of-the-art technique and the proposed technique has been provided,demonstrating the performance improvement brought by the proposed approach.

关键词： event-triggered leader-following consensus communication fault formation control unmanned aerial vehicle(UAV) experimental result

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Locate N’ Rotate: Two-Stage Openable Part Detection with Foundation Model Priors 17th

Locate N’ Rotate: Two-Stage Openable Part Detection with F...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Li, Siqi Chen, Xiaoxue Cheng, Haoyu Zhou, Guyue Zhao, Hao Tian, Guanzhong Ningbo innovation Center Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Institute for AI Industry Research Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9789819609628

Detecting the openable parts of articulated objects is crucial for downstream applications in intelligent robotics, such as pulling a drawer. This task poses a multitasking challenge due to the necessity of understanding object categories and motion. Most existing methods are either category-specific or trained on specific datasets, lacking generalization to unseen environments and objects. In this paper, we propose a Transformer-based Openable Part Detection (OPD) framework named Multi-feature Openable Part Detection (MOPD) that incorporates perceptual grouping and geometric priors, outperforming previous methods in performance. In the first stage of the framework, we introduce a perceptual grouping feature model that provides perceptual grouping feature priors for openable part detection, enhancing detection results through a cross-attention mechanism. In the second stage, a geometric understanding feature model offers geometric feature priors for predicting motion parameters. Compared to existing methods, our proposed approach shows better performance in both detection and motion parameter prediction. Codes and models are publicly available at https://***/lisiqi-zju/MOPD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Intelligent robots

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Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

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computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

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Research on the measurement device of UAV firearm unlocking force 4

Research on the measurement device of UAV firearm unlocking ...

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4th International Conference on Mechanical engineering, Intelligent Manufacturing, and Automation Technology, MEMAT 2023

作者： Yang, Mo Lin, Jing Li, Jiahao Cai, Zizhuo Ren, Haiyue Liu, Qiang School of Mechanical Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing210094 China Department of Automatic Control Systems Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia

ISBN: (纸本)9781510674820

In the current firearms dynamics research, the majority of studies focus on the extraction resistance and subsequent recoil forces, with relatively fewer studies on the unlocking force. This study focuses on the measurement of firearm unlocking force by analyzing the previously designed measurement device. By employing theoretical and dynamic simulation analyses, the variations of unlocking force over time were determined. A comparison of two sets of curves showed a high degree of coincidence, indicating the feasibility of the device in principle. Subsequently, to verify the accuracy of the measurements obtained by the device, a specific firearm was studied through simulation and experimental analysis, demonstrating the precision of the device's measurements. This structural device not only can be effectively used for measuring firearm unlocking force but also provides a new approach for experimental research on this force in firearms. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Periodic-Enhanced Informer Model for Short-Term Wind Power Forecasting Using SCADA Data

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IEEE Transactions on Sustainable Energy 2025年

作者： Liu, Zhao-Hua Li, Long-Wei Wei, Hua-Liang Li, Ming Lv, Ming-Yang Zhang, Ying-Jie Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Supervisory control and Data Acquisition (SCADA) systems can collect abundant information about wind farm operation and environment. To better make use of SCADA data, a periodic-enhanced informer model for short-term wind power forecasting using scada data is proposed. Firstly, to effectively filter out noise in SCADA data, a v-p curve-based method is adopted by incorporating a quartile approach to remove sparse outliers;a density-based spatial clustering of applications with noise (DBSCAN) algorithm is then employed to eliminate stacked outliers from the power curve. Secondly, a multi-feature input set selection method based on Maximization Information Coefficient is introduced to make better use of the SCADA system data by reducing the number of features. Thirdly, a Temporal Convolutional Network (TCN) is designed to extract the scalar projection of the input set, followed by fusing the local time stamp and global time stamp to build the periodic information enhanced prediction model embedding layer. Subsequently, the enhanced input set is fed into an informer model to predict future wind power. Finally, considering the multiple temporal scales structure characteristics present in the dataset, a multi-scale deep fusion module is established in the informer model to deeply integrate the features of different scales. It can simultaneously avoid the resource waste and overfitting problems caused by increasing the network depth. The experimental results, which are obtained from several deep learning methods on real SCADA data, demonstrate that the suggested approach has good predictive capability. © 2010-2012 IEEE.

关键词： Wind forecasting

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