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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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Stabilization of linear systems with multiple unknown time-varying input delays by linear time-varying feedback

arXiv

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arXiv 2025年

作者： Zhou, Bin Zhang, Kai Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China

This paper addresses the stabilization of linear systems with multiple time-varying input delays. In scenarios where neither the exact delays information nor their bound is known, we propose a class of linear time-varying state feedback controllers by using the solution to a parametric Lyapunov equation (PLE). By leveraging the properties of the solution to the PLE and constructing a time-varying Lyapunov-Krasovskii-like functional, we prove that (the zero solution of) the closed-loop system is asymptotically stable. Furthermore, this result is extended to the observer-based output feedback case. The notable characteristic of these controllers is their utilization of linear time-varying gains. Furthermore, they are designed entirely independent of any knowledge of the time delays, resulting in controllers that are exceedingly easy to implement. Finally, a numerical example demonstrates the effectiveness of the proposed approaches. © 2025, CC BY.

关键词： State feedback

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Distributed Observer-Based Simultaneous Fault Detection and Formation control of Multi-UAVs 42

Distributed Observer-Based Simultaneous Fault Detection and ...

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42nd Chinese control Conference, CCC 2023

作者： Su, Xiaowan Hao, Mingrui Yang, Ruohan Yue, keyuan Feng, Zhichao Northwestern Polytechnical University Xi'an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China The Rocket Force University of Engineering Xi'an710025 China

ISBN: (纸本)9789887581543

This paper studies the formation control and simultaneous fault detection of multi-UAVs. Firstly, a distributed observer is constructed for the second-order particle model of each UAV. Secondly, a novel formation controller is designed based on the distributed observer. Then, the faulty UAV is detected by the residual signal. Finally, based on Lyapunov theory and Projection Lemma, sufficient conditions for UAVs formation are obtained. The effectiveness of the proposed method is verified by simulation. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Fault detection

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Current Transformer Polarity Judgment Based on Line Parameter Fitting with Closing Transient Current 17th

Current Transformer Polarity Judgment Based on Line Paramete...

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Gu, Qianshuo Cong, Wei Wang, Feng Li, Yiquan Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250000 China Power Dispatching Control Center of Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (纸本)9789819903566

In order to solve the problem of current transformer (CT) reverse connection in power system, this paper proposes a method to judge CT polarity by fitting line parameters with closing transient current. Firstly, the relationship between line parameters and current is studied by deducing the mathematical form of closing current. By using the least square method to fit the sampling values of closing current, the line parameters are obtained. Compare the fitted line parameters with the actual line parameters. If the fitting result is consistent with the actual result, the CT polarity is correct;If the fitting result is contrary to the actual result, the CT polarity is reverse. In order to improve the accuracy of least square fitting, this paper uses matrix pencil algorithm to extract waveform features and realize decoupling among line parameters. Then, the differential equation of closing current is modified, and the remaining parameters are fitted and solved by the least square method. Finally, considering different operating environment and closing angle, the above algorithm is simulated by PSCAD and MATLAB. The simulation results show that when some sampling points are offset, the line parameters fitted by the matrix pencil algorithm are still consistent with the actual parameters. Therefore, the matrix pencil algorithm effectively improves the stability of the method and meets the needs of practical engineering. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Differential equations

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Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

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China Communications 2024年第5期21卷 297-313页

作者： Ma Shuai Yang Lei Ding Wanying Li Hang Zhang Zhongdan Xu Jing Li Zongyan Xu Gang Li Shiyin Department of Strategic and Advanced Interdisciplinary Research Peng Cheng LaboratoryShenzhen 518055China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Data-driven Intelligent Information System Laboratory Shenzhen Research Institute of Big DataShenzhen 518172China Ocean College Zhejiang UniversityZhoushan 316021China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication *** other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental *** on such a platform,we first construct a real signal dataset with ten modulation ***,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature *** also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated ***,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other *** also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

关键词： AdaBoost DBN machine learning signal demodulation

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Lane-Change Intention Prediction of Surrounding Vehicles Using BiLSTM-CRF Models with Rule Embedding

Lane-Change Intention Prediction of Surrounding Vehicles Usi...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Kai Hou, Jie Zeng, Xianlin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9781665465335

Predicting lane-change intentions of surrounding vehicles can effectively help autonomous vehicles reduce collisions caused by lane changes and ensure driving safety. Because prediction methods based on black-box models will lead to passengers' distrust of machine prediction, the intention prediction methods used to autonomous driving need to be interpretable and trustworthy. This paper presents a method for intention prediction of surrounding vehicles by using a bidirectional long short term memory network (BiLSTM) with a conditional random field (CRF) layer above it. Compared with intention prediction methods using deep network, the proposed method can find the features that contribute most to the prediction, thereby improving the interpretability and ensuring the prediction performance. In addition, by employing the transfer characteristic of the CRF layer, traffic rules and the experience of skilled drivers can be embedded to the prediction in the form of rules. Use rules to constrain the intention prediction, thereby improving the trustworthiness of prediction results. Test results on naturalistic driving dataset show that the proposed method can predict the lane-change intention with an accuracy of 97.22%, which is higher than that of Bi-LSTM. © 2022 IEEE.

关键词： Embeddings

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Unified Addressing Algorithm for Tasks in Cloud control systems 41

Unified Addressing Algorithm for Tasks in Cloud Control Syst...

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第41届中国控制会议

作者： Guan Wang Yufeng Zhan Yuanqing Xia Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information Science and Engineering University of ZaoZhuang

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of cloud computing and control theory,a new paradigm of networked control systems named cloud control systems has been proposed to satisfy the requirements of large-scale and complex *** is critical to manage large-scale tasks with personalized needs on the large number of heterogeneous ***,current TCP/IPbased addressing approach does not consider the runtime constraints of tasks,resulting highly concurrent service search,and communication between tasks will become the system *** this paper,we propose a task property encoding method which takes multi-dimensional properties into *** on the proposed encoding method,we design a uniform addressing method for tasks in the ***,we experimentally demonstrate the effectiveness of task property encoding,and the unified addressing method for tasks is more effective than other methods in the case of high task concurrency.

关键词： Cloud control systems address encoding cloud-edge-device cooperation

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intelligent Diagnosis of Planetary Gearboxes based on DAE-CNN 14

Intelligent Diagnosis of Planetary Gearboxes based on DAE-CN...

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14th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Kang, Tianbo Zhang, Mian Xie, Ruitong Chen, Jiwei Xiang, Hongbiao Wang, Yuhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China

ISBN: (纸本)9798350301359

Planetary gearboxes (PGs) are the core transmission components of complex rotating machinery. The diverse forms of internal gear faults often complicate diagnosis and maintenance work. To improve the fault diagnosis accuracy of PGs, this paper proposes a method for diagnosing PG faults based on deep autoencoders (DAE) and convolutional neural networks (CNN). The method fully utilizes the deep learning capability of DAE and combines it with the precise recognition ability of CNN for fault features. Through precise learning in the encoding layer, it achieves deep dimensionality reduction of fault features and further learns these features after dimensionality reduction by CNN. Compared to traditional CNN, the method reduces the computation parameters and resource consumption, resulting in higher precision intelligent fault diagnosis. Experimental results demonstrate that DAE-CNN exhibits stronger fault diagnosis ability than traditional networks. © 2023 IEEE.

关键词： component DAE-CNN deep learning fault diagnosis planetary gearboxes

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Research on Safety Integrity Level Assessment for Stage Machinery of Temporary Performance Site

Research on Safety Integrity Level Assessment for Stage Mach...

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2023 International Conference on Culture-Oriented Science and Technology, CoST 2023

作者： Hu, Yubin Su, Zhibin Wang, Zixiao Wang, Huiqin School of Information and Communication Engineering Communication University of China China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (纸本)9798350357998

The safety assessment of stage performing arts equipment for the temporary site is an urgent task to be solved. In this paper, the lifting equipment is chosen for risk analysis, safety circuit identification and safety integrity level (SIL) calculation. The Hazard and Operability Study(HAZOP) and Layer Of Protection Analysis(LOPA)-based method is studied to get the expected SIL level of the related safety loops. In addition, the fault tree and Markov model methods are used to verify the actual SIL level under the existing loop structure respectively. This study provides the theory and data basis for the development of safety requirements and evaluation standards for the temporary theater of stage machinery, which has certain theoretical significance and application value. © 2023 IEEE.

关键词： Risk analysis

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