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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Xinyu Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811966125

Aiming at the research status of formation control and cooperative guidance technology of multi unmanned aircrafts, this paper introduces various methods of formation control technology and cooperative guidance technology. It also expounds the characteristics of formation control methods such as graph theory, leader-follower formation, behavior strategy, virtual structure, artificial potential field mode and consistency mode, as well as independent, centralized and distributed cooperative guidance methods. Then the application status and technical development of intelligent methods in multi vehicles formation control and cooperative guidance are introduced. At the same time, this paper compares the advantages and problems of various methods, and prospects the future development direction of this field. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graph theory

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Data-driven Anomaly Detection Method Based on Similarities of Multiple Wind Turbines

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Journal of Modern Power systems and Clean Energy 2024年第3期12卷 803-818页

作者： Xiangjun Zeng Ming Yang Chen Feng Mingqiang Wang Lingqin Xia the College of Electrical Engineering&New Energy China Three Gorges UniversityYichang 443002China the Key Laboratory of Power System Intelligent Dispatch and Control Shandong UniversityJinan 250061China

The operating conditions of wind turbines(WTs)in the same wind farm(WF)may share similarities due to their shared manufacturing process,control strategy,and operating ***,the similarities of WTs are seldom considered in WT anomaly detection,resulting in the disregard of useful *** paper proposes a method to improve the reliability and accuracy of WT anomaly detection using the supervisory control and data acquisition(SCADA)data of multiple WTs in the same ***,a similarity assessment method based on a comparison of different observation time series is proposed,which objectively quantifies the similarities of WT operating ***,the SCADA data of the target WT and selected WTs that are similar are used to establish several estimation models through a long short-term memory(LSTM)*** models that exhibit good estimation performance are used to construct a combined estimation model that estimates the variations in the monitored variables of the target ***,an anomaly detection method that jointly compares the effective value and information entropy of the residuals is proposed to identify *** effectiveness and accuracy of the proposed method are verified using the data of two actual WFs.

关键词： Anomaly detection information entropy long short-term memory similarity assessment wind farm wind turbines

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Collaborative Estimation of Multi-source Heterogeneous Moving Sensors for UAV Cluster 5th

Collaborative Estimation of Multi-source Heterogeneous Movin...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Yang, Xiangyu Song, Chuang Chen, Linxiu Hao, Mingrui Zhang, Hang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811939976

In the cooperative combat mission of UAV cluster, the collaborative estimation of targets by airborne multi-source heterogeneous sensors can make the utmost of the multivariate detection performance of moving sensors placed in multiple spatial positions in complex confrontation environments, in order to deal with the problem of independent estimation failure of sensors carried by single aircraft under the multiple compound interference of non-cooperative targets. In this paper, the typical target motion model, estimation model and interference model are established, then a collaborative estimation method of airborne target detection sensors with different detection accuracy and different interference countermeasure capability is designed for each aircraft in the UAV cluster, based on spatial allocation strategy, nonlinear filtering, interference detection, consistency correlation and information fusion. It is verified by Monte Carlo simulation study that this method can guarantee the obtainment of continuous and accurate guidance information for each aircraft in the cluster, so as to improve the strike accuracy of each UAV and complete the strike mission. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Active Distribution Grid Risk Prevention and control Method Based on Biological Immune Mechanism 3rd

Active Distribution Grid Risk Prevention and Control Method ...

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3rd International Joint Conference on Energy, Electrical and Power Engineering, CoEEPE 2023

作者： Zhao, Hui Ma, Jun Yue, Youjun Wang, Hongjun Tianjin Key Laboratory of Complex System Control Theory and Tianjin University of Technology Tianjin China

ISBN: (纸本)9789819739394

Aiming at the insufficient optimization ability of traditional active distribution network (ADN) fault recovery, a combination of immune mechanism and immune genetic algorithm is proposed for risk prevention and control. First, a risk assessment model is constructed from the perspective of reliability of equipment operation and consequences of faults;second, for the first N scenarios with higher risk, a fault pre-recovery scheme is established with the objectives of restoring the most power supply, minimizing the number of switching times, and minimizing the network loss, and the immune genetic algorithm is used to solve the problem. The N scenarios are recorded in the set of expected incidents to expand the immune memory cell library;finally, the simulation is carried out using the IEEE 33-node distribution network model as an example, and the simulation results show the feasibility of the proposed risk prevention and control strategies and the algorithms used, which lays a foundation for the subsequent fast and accurate recovery of power supply. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electric power distribution

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Static Unstable STT Overload control on High-order Fully Actuated system Theory 6

Static Unstable STT Overload Control on High-order Fully Act...

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Liu, Xinyu Hao, Mingrui Zhen, Yan Fan, Yu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

This article proposes a joint overload controller for pitch and yaw channels on the high-order fully actuated system theory for a nonlinear lateral and longitudinal static unstable STT aircraft model. Firstly, a second-order fully actuated system model for aircraft overload was derived, and an optimal control method for lateral and longitudinal overload was designed. Through mathematical simulation verification of this controller and traditional PID controller, it is shown that the PID control method has significant shortcomings in nonlinear aircraft with coupling. However, high-order fully actuated system theory control method can better adapt to nonlinear and static instability problems, achieve stable tracking of aircraft overload commands, and have better rapidity. © 2023 IEEE.

关键词： system theory

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Autonomous relative optical navigation based on unified modeling of external systematic errors

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Chinese Journal of Aeronautics 2024年第3期37卷 282-289页

作者： Dayi WANG Bowen SUN Maodeng LI Jiaxing LI Haiyin ZHOU Beijing Institute of Spacecraft System Engineering Beijing 100191China College of Sciences National University of Defense TechnologyChangsha 410073China National Key Laboratory of Space Intelligent Control Beijing Institute of Control EngineeringBeijing 100191China

To solve the problem that external systematic errors of the optical camera cannot be fully estimated due to limited computing resources,a unified dimensionality reduction representation method for the external systematic errors of the optical camera is proposed,and autonomous relative optical navigation is *** camera translational and misalignment errors are converted into a three-dimensional rotation error,whose differential model can be established through specific attitude control and appropriate ***,the rotation error and the relative motion state are jointly estimated in an augmented Kalman filter *** with the traditional method that estimates the camera translational and misalignment errors,the proposed method reduces the computational complexity in that the estimated state dimension is ***,as demonstrated by numerical simulation,the estimation accuracy is improved significantly.

关键词： Unified model systematic errors Optical navigation Observability analysis Calibration

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Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating with Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional method suffers from poor position and speed estimation accuracy under dynamic conditions, and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this paper. Differing from conventional method, a reduced-order linear state equation encompassing rotor position, speed and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process, but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameters variations. Additionally, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy.1 © 1986-2012 IEEE.

关键词： Permanent magnets

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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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A joint sparse Bayesian learning for wideband DOA estimation

A joint sparse Bayesian learning for wideband DOA estimation

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2024 Conference on Spectral Technology and Applications, CSTA 2024

作者： Zhao, Yonghong Liu, Jisong Wang, Junlong Dong, Shuxin Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Department of Automation and Information Engineering Xi'an University of Technology Shaanxi Xi'an710048 China

ISBN: (纸本)9781510683082

Wideband direction of arrival (DOA) estimation using sensor array is a noteworthy problem frequently occurring in many applications involving radar, sonar, and communication. We present a wideband DOA method based on a sparse Bayesian learning of multiple sub-bands jointly with the redundant dictionary matrix at the reference frequency. Explicitly enforcing the focusing operation and the singular value decomposition (SVD) to sensor measurements is motivated by a desire to decrease the computational complexity and storage capacity. A joint sparse Bayesian learning framework is proposed to deal with multiple sub-bands under one segment to obtain the DOA information. Moreover, the proposed method can be directly extended to multiple segments. Comparing to other wideband DOA estimation methods, the proposed method has the advantages of increased resolution, higher accuracy, and correlation of the sources, as well as not requiring the initial angles for the focusing matrix. Simulations are provided to show the effectiveness and improved performance of the proposed method. © 2024 SPIE.

关键词： Direction of arrival

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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