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Optimal Cooperative Secondary control for Islanded DC Microgrids via a Fully Actuated Approach

IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 405-417页

作者： Yi Yu Guo-Ping Liu Yi Huang Peng Shi IEEE Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Electrical and Mechanical Engineering the University of AdelaideSA 5005Australia Research and Innovation Centre Obuda University1034 BudapestHungary

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

关键词： DC microgrids distributed control high-order fully actuated system approach linear quadratic regulator microgrid modeling secondary control

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Optimal Multi-agent Collision-Free Path Planning with Temporal Logic Constraints 5th

Optimal Multi-agent Collision-Free Path Planning with Tempo...

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

作者： Zheng, Yiwei Liu, Zhaocong Lai, Aiwen Yu, Xiao Lan, Weiyao Department of Automation Xiamen University Fujian Xiamen361005 China The Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9789811939976

In this paper, we present a novel optimal multi-agent collision-free path planning algorithm (OMPATL) for the problem of multi-robot path planning with temporal logic constraints. Given a high-level mission specification in the form of linear temporal logic (LTL), OMPATL can automatically synthesize a set of trajectories for the multi-agent system (MAS), which achieves the collision avoidance among agents and minimizes the cost of the maximum traveling time between successive satisfactions. To synthesize the optimal trajectories, the motion of all agents, together with the mission area, is modeled as a weighted team transition system (TS) with a set of atomic propositions (APs). If the collision avoidance were not required, the optimal trajectories would be easily synthesized by an algorithm such as shortest paths. However, once the multi-agent systems are required to be safety-critical and collision-free, these trajectories may become infeasible. In OMPATL, a strategy is proposed for adding a set of transitions including "wait" and "go-back" to each individual TS based on the optimal run which does not consider collision avoidance. Then, the states and transitions with collisions can be removed such that the optimal collision-free trajectories are founded by the synthesis algorithm. The synthesized run balances collision avoidance, mission fulfillment, and optimality. The optimal run is synthesized offline and online adjustments are not needed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Warship Object Detection in Remote Sensing Images with Improved YOLOv5

Warship Object Detection in Remote Sensing Images with Impro...

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2023 China Automation Congress, CAC 2023

作者： Liu, Caiyuan Li, Yuan Chen, Linxiu Guan, Weili School of Automation Beijing Institute of Technology Beijing100081 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9798350303759

Aiming at the task of detecting ships on the sea surface in remote sensing images, there are a lot of disturbances such as variable object sizes, cloud occlusion, complex image backgrounds, and different ship orientations, etc. In this paper, we propose a ship rotating object detection network based on the improved YOLOv5, which is constructed through the strategies of introducing Swin Transformer as a feature extraction network to enhance the feature extraction performance of the network, introducing a rotating detection head to realize the detection of the rotation angle, and modifying the network loss function to accelerate the convergence of the network. The network finally achieves a 71.7% map on ShipRSImageNet validation set, which is an improvement of 2.4% compared with the original network model. The network proposed in this paper solves the problem that the YOLOv5 algorithm is unable to detect rotating objects, and the network based on the self-attention mechanism is used to further enhance the ability to detect small objects. Finally, a ship object detector that can be used in real remote sensing satellite images is obtained. © 2023 IEEE.

关键词： Feature extraction

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Feature Layer Fusion of Linear Features and Empirical Mode Decomposition of Human EMG Signal

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Journal of Electronic science and technology 2022年第3期20卷 257-269页

作者： Jun-Yao Wang Yue-Hong Dai Xia-Xi Si the School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu611731China the Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu611731China

To explore the influence of the fusion of different features on recognition,this paper took the electromyography(EMG)signals of rectus femoris under different motions(walk,step,ramp,squat,and sitting)as samples,linear features(time-domain features(variance(VAR)and root mean square(RMS)),frequency-domain features(mean frequency(MF)and mean power frequency(MPF)),and nonlinear features(empirical mode decomposition(EMD))of the samples were *** feature fusion algorithms,the series splicing method and complex vector method,were designed,which were verified by a double hidden layer(BP)error back propagation neural *** show that with the increase of the types and complexity of feature fusions,the recognition rate of the EMG signal to actions is gradually *** the EMG signal is used in the series splicing method,the recognition rate of time-domain+frequency-domain+empirical mode decomposition(TD+FD+EMD)splicing is the highest,and the average recognition rate is 92.32%.And this rate is raised to 96.1%by using the complex vector method,and the variance of the BP system is also reduced.

关键词： Complex vector method electromyography(EMG)signal empirical mode decomposition feature layer fusion series splicing method

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Fault Diagnosis with spacecraft High-Dimensional Data Based on Machine Learning

Fault Diagnosis with Spacecraft High-Dimensional Data Based ...

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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021

作者： Liang, Hanyu Liu, Yun Liu, Chengrui Liu, Wenjing Li, Wenbo Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory Beijing China

ISBN: (纸本)9781665401159

In order to ensure the safe, reliable and stable operation of spacecraft, this paper studies the fault diagnosis of spacecraft high-dimensional data by applying the machine learning technology, aiming at the characteristics of spacecraft, such as closed-loop fault propagation, few fault samples and limitation of on-orbit computing capability. For the experimental data under the typical failure modes of spacecraft sensors and actuators, this paper will use some machine learning algorithms like K-Nearest Neighbor (KNN), Bayesian classifier, KNN based on Principal Component Analysis (PCA+KNN), to analyze fault diagnosis and to make a comparative analysis of the results. The results show as follows: it can reach better accuracy by using supervised learning algorithms in fault diagnosis classification;the dimensionality reduction can accelerate the calculation, but at the same time it will lose diagnostic accuracy, especially for highly-coupled and high-dimensional data;in the algorithm design, the task requirements and application conditions should be considered comprehensively, meanwhile the optimal fault diagnosis model can be selected by balancing the accuracy and computing time. © 2021 IEEE.

关键词： Failure analysis

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Ozone oxidation of 4H-SiC and flat-band voltage stability of SiC MOS capacitors

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Chinese Physics B 2022年第11期31卷 500-509页

作者： Zhi-Peng Yin Sheng-Sheng Wei Jiao Bai Wei-Wei Xie Zhao-Hui Liu Fu-Wen Qin De-Jun Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116024China State Key Laboratory of Materials Modification by Laser Ionand Electron Beams(Ministry of Education)Dalian University of TechnologyDalian 116024China

We investigate the effect of ozone(O_(3))oxidation of silicon carbide(SiC)on the flat-band voltage(Vfb)stability of SiC metal–oxide–semiconductor(MOS)*** SiC MOS capacitors are produced by O_(3)oxidation,and their Vfbstability under frequency variation,temperature variation,and bias temperature stress are *** ion mass spectroscopy(SIMS),atomic force microscopy(AFM),and x-ray photoelectron spectroscopy(XPS)indicate that O_(3)oxidation can adjust the element distribution near SiC/SiO_(2)interface,improve SiC/SiO_(2)interface morphology,and inhibit the formation of near-interface defects,*** addition,we elaborate the underlying mechanism through which O_(3)oxidation improves the Vfbstability of SiC MOS capacitors by using the measurement results and O_(3)oxidation kinetics.

关键词： SiC MOS capacitors ozone oxidation bias temperature instability Deal-Grove model

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Recent Patents for control Devices of Fluid Pressure

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Recent Patents on Engineering 2022年第3期16卷 43-53页

作者： Xie, Baocheng Wang, Yi Li, Chaoxiang Zhang, Hanyang Zhang, Yongxing Su, Haobin Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin150080 China Beijing Institute of Control Engineering Beijing200085 China

Fluid pressure, an important parameter of fluid flow, affects the control accuracy and stability of fluid transmission. The control devices of fluid pressure are widely applied to the mechanical transmission control, which is the main means to change the fluid pressure and improve control accuracy and stability in the mechanical transmission system. To control the accuracy and stability of the fluid transmission, the pressure control device is divided into pressure reduction devices, pressurization devices, and stabilizing pressure devices. The characteristics of pressure control devices with different functions are analyzed from the structure of the device. Thus, more and more attention has been paid to the control devices of fluid pressure. To meet the increasing requirement of control accuracy and stability of fluid transmission, the control devices of fluid pressure, such as pressure reduction devices, pressurization devices, and stabilizing pressure devices, are being improved continuously. This paper reviews various current representative patents related to pressure reduction devices, pressurization devices, and stabilizing pressure devices of fluid pressure. By investigating various patents on the control devices of fluid pressure, the main current existing problems of the pressure control devices, such as low control accuracy and poor stability, are summarized and analyzed. Furthermore, the development trend of the control devices of fluid pressure has also been discussed. The optimization of the structure and function of the control devices of fluid pressure is conducive to improve the control accuracy and stability of transmission of the fluid. More relevant patents will be invented in the future. © 2022 Bentham science Publishers.

关键词： Stability

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Design and Experimental Validation of a Worm-Like Tensegrity Robot for In-Pipe Locomotion

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Journal of Bionic Engineering 2023年第2期20卷 515-529页

作者： Xiaolin Dai Yixiang Liu Wei Wang Rui Song Yibin Li Jie Zhao School of Control Science and Engineering Shandong UniversityJinan250061China Engineering Research Center of Intelligent Unmanned System of Ministry of Education Jinan250061China Shandong Research Institute of Industrial Technology Jinan250061China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150080China

Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and *** soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties due to their reliance on high-performance soft *** structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings,which combines the advantages of both rigid structures and soft *** applying tensegrity structures into robotics,this paper proposes a novel worm-like tensegrity robot for moving inside ***,a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is ***,the optimal parameters of the module are obtained based on the tensegrity *** deformation ability of the tensegrity module is tested ***,the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in *** performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe,vertical pipe,and elbow *** results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance,mobility,and adaptability although with simple structure and low cost.

关键词： Bio-inspired robot Soft robot application Tensegrity structure Pipe crawling

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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