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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Zhiheng Zhou, Rui Chen, Jinyong Zhang, Ning School of Automation Science and Electrical Engineering Beihang University Beijing100083 China Science and Technology on Aircraft Control Laboratory AVIC Xi’an Flight Automatic Control Research Institute Xi’an710065 China

ISBN: (纸本)9789811966125

The confrontation between UAV swarms will be an important combat style in the future, and a reasonable division of such a target air fleet is instructive to the deployment of our own resources. In this paper, we combine the genetic fuzzy clustering and the cluster validation to achieve autonomous grouping of the UAV swarm. Firstly, the flight state parameters such as position, speed, and yaw angle are used as characteristic components to measure the differences among UAVs. Then, the proposed approach establishes a mathematical model for grouping of the UAV swarm by fuzzy C-means algorithm. In addition, we compare five advanced clustering validity indexes and a clustering validation method based on graph theory, from which an evaluation criterion more applicable to grouping of the UAV swarm is selected. Finally, numerical simulations are performed to verify that the proposed approach can divide the air fleet autonomously and rationally in complex task scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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ST-Petri: A Visual Executable Semantic Model for PLC Structured Text Language 22

ST-Petri: A Visual Executable Semantic Model for PLC Structu...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Hu, Xiaoyu Liang, Yonghui Zhu, Shibo Li, Hui Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798331527471

As very important controllers in automated factories, the correctness and safety of Programmable Logic controller (PLC) and their programs determine the stability of the production process. Structured Text (ST) is one of the most widely used PLC programming languages. However, there are not enough formal semantics and different venders may have their own implementations. In this work, a visual executable semantic model ST-Petri for ST has been proposed. The model uses Petri nets to formally represent ST semantics while using graphs to visualise program control flow. To validate the correctness of the semantic model, we use programs from Github and mutations of existing source programs as a test set to execute and compare the results with the open source OpenPLC platform. Experimental results show that ST-Petri has significant advantages in terms of compilation pass rate and error indication as a semantic model and a ST program compiler. © 2024 IEEE.

关键词： Petri nets

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Bearing-Based Containment control of Multi-agent Systems with Disturbances 7th

Bearing-Based Containment Control of Multi-agent Systems wi...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Duan, Mengmeng Yang, Ziwen Zhu, Shanying Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9789819733392

In this paper, a bearing-based containment control problem of multi-agent systems with disturbances is studied. The nonlinearity of the bearing results in the existence of nonlinear time-varying parameters in the closed-loop system. When the leaders are stationary, under the sufficient conditions on the disturbances and the connectivity of the directed sensing graph, the boundedness of the nonlinear time-varying parameters is rigorously proved, with which it is shown that the containment error converges to zero asymptotically. When the leaders are moving, by using the properties of the bearing and the projection, it is proved that the containment error is uniformly ultimately bounded and can be reduced by adjusting the edge weight. Numerical examples illustrate the effectiveness of the proposed controller. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Plume Finding with Frontier-Based Planner 6

Plume Finding with Frontier-Based Planner

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Zhang, Xin-Kai Li, Ji-Gong Yang, Jing School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin Tianjin China School of Information Technology Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9798350356618

Toxic/hazardous gas leaks seriously jeopardize public safety and the ecological environment, and how to utilize drones with on-board gas sensors to quickly detect gas plumes at an early stage of a gas leak and take timely measures can effectively prevent the expansion of the accident. Traditional plume finding methods have the disadvantages of poor targeting, long search times, and repeated exploration in some areas. In view of this, this paper proposes a method of plume finding with frontier-based planner, where a heuristic function is designed to select optimal observation points and thus plan path to search plume. Here an air-mass path model is constructed to estimate the region that would likely be observed by the UAV at a candidate observation site on the frontier, and the area of the unknown part in the region is considered as the environmental exploration gain. The change in flight direction and the distance traveled by the UAV are used as environmental exploration costs when it will fly from its current pose to the candidate observation site. Simulation results show that the proposed frontier-based exploration method for plume finding has good performance in odor source localization tasks in outdoor environments. © 2024 IEEE.

关键词： Direct air capture

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Fault prediction of electric vehicle charging stations based on cooperative game strategy and DBO-BiLSTM 6

Fault prediction of electric vehicle charging stations based...

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6th IEEE Advanced Information Management, Communicates, Electronic and automation control Conference, IMCEC 2024

作者： Tian, Liguo Shang, Chunhu Li, Meng Chen, Qingbin Tianjin University of Technology and Education College of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350316520

Aiming at the problem of high failure rate of electric vehicle charging pile, an electric vehicle charging pile failure prediction method based on cooperative game strategy and dung beetle optimisation algorithm-bidirectional long and short-term memory network (DBO-BiLSTM) is proposed. Firstly, the outliers are handled by parameter statistical distribution, the missing values are handled by mean padding, and the normalisation operation is performed on the processed data;secondly, multiple single-assignment methods are selected to calculate the feature weights, the combined weights are calculated by the cooperative game strategy, and the parameter feature matrix is enlarged;and then, the DBO-BiLSTM model is constructed, and under the simulation experiments, the accuracy rate of the training set and test set, the F1 coefficients are 0.89, 0.89, 0.90 and 0.89, ***, relevant comparison experiments are constructed, and the results show that the proposed model has better performance, which verifies the effectiveness and reasonableness of the proposed model. © 2024 IEEE.

关键词： Brain

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Research on Smart Photovoltaic Power Station control System Based on DCS Architecture

Research on Smart Photovoltaic Power Station Control System ...

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2024 International Conference on Computer Communication, Networks and Information Science, CCNIS 2024

作者： Zhan, Lei Chn Energy Zhishen Control Technology Co. Ltd. Beijing Engineering Research Center of Power Station Automation State R&D Center of Control System and Information Security Technologies for Energy Industry Beijing102211 China

ISBN: (纸本)9798331507046

Aiming at the operation and maintenance management and control issues of large-scale photovoltaic power stations, a smart photovoltaic power station control system based on DCS architecture was studied. In terms of system architecture design, the design idea based on the 'cloud-edge-end' architecture is adopted, and some core equipment and data storage devices in the site are placed in the cloud to achieve centralized management and storage of data. At the same time, some computationally intensive tasks are processed in the cloud to reduce the computing pressure on edge devices. Applying this system to the control of photovoltaic power plants can achieve precise control of operation and maintenance data, and enable the identification and accurate processing of different faults. Comparing the fault identification algorithm used in this system with other algorithms, the results prove that the fault identification accuracy of this algorithm can reach 100℅, creating a large amount of economic benefits for the stable operation of photovoltaic power plants. © 2024 IEEE.

关键词： Ferroelectric RAM

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Fault Modeling and Diagnosis for Spacecraft Attitude control System Using Deep Learning

Fault Modeling and Diagnosis for Spacecraft Attitude Control...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Guo, Pengyu Hu, Qinglei Wu, Huai-Ning Duan, Chao Chen, Bin Zhang, Peng School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Peng Cheng Laboratory Shenzhen518000 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789811966125

The health monitoring system is significant for the reliable operation of spacecraft. In this paper, various fault models for controlling torque gyroscopes are established, and the learning network is trained with uniformly sampled data of fault. Then a data-driven fault diagnosis method based on deep learning is proposed. The method fully extracts the features to describe the classification of the multi-modal actuator faults, and trains the fault model with a large amount of spacecraft data under actuator faults. Then the rapid detection and classification of actuator faults are realized by the unknown fault model. Specifically, a spacecraft attitude control model is established to generate the sample data for the problem of insufficient fault data. Besides, the stack encoder is used to automatically reduce the data dimension and extract the main features from each set of data. Further, softmax classifier is introduced for fault model training. Finally, numerical simulations are illustrated to verify the reliability of the fault diagnosis method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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Practical Predefined-Time Consensus control for High-Order Multiagent Systems Via Output Feedback

Practical Predefined-Time Consensus Control for High-Order M...

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2024 China automation Congress, CAC 2024

作者： Li, Xiaoting Cao, Xiaotong Li, Yueti Jiao, Dexin Wang, Chen Zou, An-Min College of Engineering Shantou University Shantou China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350368604

This paper considers the problem of practical predefined-time (PPT) consensus control for a class of high-order nonlinear multiagent systems. With the help of the smooth time-varying function-based technique, the leader’s state and the follower’s unmeasurable states are estimated by introducing PPT observers. Then, a PPT output feedback consensus control algorithm with no singularity and discontinuity is proposed based on the observers. Finally, the effectiveness of the designed output feedback PPT consensus control scheme is validated by virtue of an illustrative numerical example. © 2024 IEEE.

关键词： Feedback

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Vision-Based Adaptive Prescribed-Time control of UAV for Uncooperative Target Tracking with Performance Constraint

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Journal of Systems Science & Complexity 2024年第5期37卷 1956-1977页

作者： SHE Xuehua MA Hui REN Hongru LI Hongyi School of Automation and the Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of TechnologyGuangzhou 510006China School of Mathematics and Statistics Guangdong University of TechnologyGuangzhou 510006China College of Electronic and Information Engineering and Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest UniversityChongqing 400715China

This paper discusses the uncooperative target tracking control problem for the unmanned aerial vehicle(UAV)under the performance constraint and scaled relative velocity constraint,in which the states of the uncooperative target can only be estimated through a vision *** the limited detection range,a prescribed performance function is designed to ensure the transient and steady-state performances of the tracking ***,the scaled relative velocity constraint in the dynamic phase is taken into account,and a time-varying nonlinear transformation is used to solve the constraint problem,which not only overcomes the feasibility condition but also fails to violate the constraint ***,the practically prescribed-time stability technique is incorporated into the controller design procedure to guarantee that all signals within the closed-loop system are *** is proved that the UAV can follow the uncooperative target at the desired relative position within a prescribed time,thereby improving the applicability of the vision-based tracking *** results have been presented to prove the validity of the proposed control strategy.

关键词： Nonlinear transformation performance constraint prescribed-time tracking uncooperative target vision-based measurement

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