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Resilient Formation control Based on Watermarks for Networked Quadrotors under Deception Attacks

IEEE Transactions on Vehicular Technology 2025年第6期74卷 8839-8850页

作者： Zhan, Weiwei Miao, Zhiqiang Zeng, Jianxin Chen, Yanjie Wu, Zheng-Guang He, Wei Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China Fuzhou University School of Mechanical Engineering and Automation Fuzhou350108 China National Engineering Research Center of Robot Visual Perception and Control Technology Changsha410082 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Institute of Artificial Intelligence Beijing100083 China

This article addresses the problem of formation control of networked UAVs under deception attacks. A lightweight resilient formation control framework based on watermarks is proposed to achieve the desired formation configuration without extra monitoring attack status. Since deception attacks are covert, the shared information is watermarked before transmission to establish the protocol among networked UAVs. To facilitate the resilient formation controller design, a decoder is first developed to decipher the inverse transformation of deception attacks, where the watermark is the criterion for approximating the inverse transformation. The Gauss error function is introduced to eliminate some unrealistic input commands under deception attacks, obtaining the predefined input performance. Then, a resilient formation controller is developed to guarantee the global boundedness of all signals within the inner-loop and outerloop system, while the formation error converges to a small neighborhood of zero by solving the linear matrix inequality. Two challenging deception attack examples in simulations and experiments are conducted to verify the effectiveness and performance of the proposed resilient formation control framework. © 1967-2012 IEEE.

关键词： Inverse transforms

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Emotion recognition based on CNN-SVM from EEG signals 5

Emotion recognition based on CNN-SVM from EEG signals

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5th Asia Symposium on Image Processing, ASIP 2023

作者： Jia, Yuyu Han, Chunxiao Tong, Wenhui Pei, Yue Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin China

ISBN: (纸本)9798350323429

Emotion recognition is an important research directions in the field of artificial intelligence. In this paper, we adopted deep learning methods to try to improve the performance of emotion recognition. First, we designed an experiment to induce three different emotions by video footage and collected corresponding EEG signals. Then, CNN-SVM algorithms were adopted to classify positive, neutral and negative emotions. Finally, the recognition performance of CNN-SVM for three-class emotion recognition was verified. It is found that CNN-SVM achieves a highest recognition accuracy of 99.98% and an average recognition accuracy of 98.53%, which is better than CNN alone. © 2023 IEEE.

关键词： Emotion Recognition

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Automatic Schizophrenia Detection from Scalp EEG Using CNN with Wide Convolutional Kernel and ELM 5

Automatic Schizophrenia Detection from Scalp EEG Using CNN w...

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5th Asia Symposium on Image Processing, ASIP 2023

作者： Wei, Chun Qin, Yingmei Liu, Jing Jiang, Lijie Che, Yanqiu Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin China

ISBN: (纸本)9798350323429

Detection of schizophrenia is of great significance in clinical practice. In conventional machine learning methods, manual feature extraction is required, which is a hard and time-consuming task. This paper proposes a hybrid model consisting of a convolutional neural network (CNN) with a wide convolution kernel and an extreme learning machine (ELM). By changing the size of the convolution kernel to form a suitable wide convolution kernel, and automatically extracting and optimizing the features of the scalp electroencephalogram (EEG), the performance of the model is effectively improved and accurate detection of schizophrenia is achieved. The input of this model is the original multi-channel EEG picture after short-time Fourier transform, and the output are two types of classification labels for schizophrenia and healthy people. In the end, the detection accuracy of schizophrenia reached 95.59%. This model has a powerful advantage in detecting schizophrenia. © 2023 IEEE.

关键词： Electroencephalography

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Fault diagnosis for wasterwater treatment plant based on an improved support vector data description method

Fault diagnosis for wasterwater treatment plant based on an ...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Zhou, Meng Song, Weiwei Wang, Jing Wang, Chang North China University of Technology School of Electrical and Control Engineering Beijing China Beijing Aerospace Automation Research Institute Beijing China

ISBN: (纸本)9798350337754

In this paper, a fault detection method based on improved support vector data description is proposed for wastewater treatment plants. First, an improved Multi-Kernel Support Vector Data Description (MKSVDD) method is presented in which multicore-kernel functions are combined with the traditional support vector data description method. This can make the model more adaptable to different input samples, allowing it to have both learning and generalization capabilities. Then, the parameters of the MKSVDD are optimizted by Sparrow Search Algorithm (SSA), which overcomes randomness and uncertainty of human manual adjustment parameters. Finally, simulation results are given to demonstrate the effectiveness of the proposed method. Nine types of fault data sets generated by the Benchmark Simulation Model 1 (BSM1) are used and simulations results show that the model is more adaptable to the samples and has better indicators for anomaly detection compared to the original algorithm. © 2023 IEEE.

关键词： Wastewater treatment

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Research on the Flux-weakening Capability of the Reverse-salient Permanent Magnet Synchronous Motor 26

Research on the Flux-weakening Capability of the Reverse-sal...

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26th International Conference on electrical Machines and Systems, ICEMS 2023

作者： Zhao, Xiaokun Zhang, Cheng Wang, Weinan Kou, Baoquan Zhu, Liangkuan Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Institute of Technology Department of Electrical and Automation Harbin China

ISBN: (纸本)9798350317589

Permanent magnet synchronous motors (PMSMs) offer the benefits of high torque density and a superior power factor. Nevertheless, the challenge lies in the inherent difficulty of adjusting the permanent magnet flux. To address this issue, this paper analyzes the influence of electromagnetic parameters on the constant-power speed range (CPSR). First, the analysis focuses on the influence of d-axis inductance and saliency ratio, aiming to establish a design method for achieving a wide CPSP in PMSMs. Second, based on the electromagnetic parameter requirements, a reverse-salient PMSM is proposed and its working principle is explained. Finally, the electromagnetic characteristics, including torque and the CPSP, are determined through the application of the finite element method (FEM). The obtained results confirm that the reverse-salient PMSM achieves a CPSP of 7:1, thus validating the accuracy of the theoretical analysis. © 2023 IEEE.

关键词： Finite element method

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Research on Intelligent Monitoring and Irrigation System for Farmland Based on IoT and 5GTechnology 8

Research on Intelligent Monitoring and Irrigation System for...

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8th International Conference on automation, control and Robotics engineering, CACRE 2023

作者： Lu, Guangda Dai, Jianyi Qin, Zhuanpin Guo, Tinghang Han, Yu Wei, Mingzhi Automation and Electrical Engineering College Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350302776

A farmland intelligent monitoring and irrigation system based on the Internet of Things and 5G technology is designed. The system mainly includes two templates: intelligent monitoring system and intelligent control system, in which the intelligent monitoring system is mainly responsible for detecting soil temperature and humidity and trace elements such as nitrogen, phosphorus and potassium, and the intelligent control system is mainly responsible for remote operation of intelligent irrigation. The system measures soil temperature, humidity and trace elements such as nitrogen, phosphorus and potassium through the sensors in the intelligent monitoring section, and uses 5G wireless transmission technology to send the data collected by the sensors to the Internet of Things, which then transmits the collected information to a mobile app. The system can solve the shortcomings of traditional irrigation methods which are cumbersome and seriously inefficient in irrigating agricultural facilities. © 2023 IEEE.

关键词： Soil temperature

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XSpace: Self-learning platform for implementation of digital control algorithms 14

XSpace: Self-learning platform for implementation of digital...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Caceres, Pablo Cardenas Cieza Huane, Leslie Y. Horna Vilcahuaman, Ingrid M. Pauyac Estrada, Claudia R. Casano, Celso De-La-Cruz Tafur Sotelo, Julio C. Pontificia Universidad Catolica Del Peru Department of Engineering Electronics Section Lima Peru Degree Program Pontificia Universidad Catolica Del Peru Department of Engineering Control and Automation Master Engineering Lima Peru

ISBN: (纸本)9798350399431

In the electronic engineering undergraduate program, Peruvian universities offer different theoretical courses of Automatic control that do not present enough practical approach to the algorithms that are studied during the progress of these courses;however, the approach to implementation is very important to achieve good performance in the industry and researching. In this work is presented XSpace, an innovative and friendly platform which consists of a robust hardware that allows the student to take it home;this way, the student is given the opportunity to implement digital control algorithms learned in the theoretical classes. The effectiveness of this platform is shown using a proposed methodology which evidences greater interest, efficiency and efficacy in students at the Automatic control area. This project was implemented in the 'control Systems' course at Pontificia Universidad Catolica del Peru (PUCP) from 2020 to 2022. Results are presented through a student survey and a history of average grades during the academic periods the platform was employed. © 2023 IEEE.

关键词： Students

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Odor Plume Direction Estimation via Gas Sensor Array

Odor Plume Direction Estimation via Gas Sensor Array

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2023 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2023

作者： Li, Jin-Sheng Li, Ji-Gong School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350309003

The direction of the odor plumes is very helpful for robots to preform odor source localization task. To address issues of that wind measurement equipment is not able or convenient to carry on the robots, this paper proposes a method for estimating the incoming direction of the odor plume with a gas sensor array. Firstly, a model for estimating the incoming direction of the odor plume was established via the positional relationship between gas sensors in the sensor array. Secondly, by using the output responses of the gas sensors in the array, the time delay between gas sensors was calculated via cross-correlation method. Thirdly, the solution of the model was solved using the Levenberg-Marquette method. Finally, the results of gas sensor arrays in different distribution patterns indicate that our proposed method can estimate the incoming direction of odor plume effectively. © 2023 IEEE.

关键词： Gases

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Improved YOLOv3 and U-Net Based Pipetting Abnormal Condition Identification and Pipetting Region Segmentation

Improved YOLOv3 and U-Net Based Pipetting Abnormal Condition...

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2023 European Conference on Communication Systems, ECCS 2023

作者： Zhang, Zhiyu Li, Huiyan Liu, Yeming Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350323344

To improve the reliability of micro pipetting in automatic pipetting workstations, this paper analyzes and investigates the problems related to abnormal condition recognition and pipetting volume detection during pipetting using deep learning models. Firstly, the YOLOv3 network model is designed to be lightweight, and the DarkNet-53 network, which is the backbone of the network structure for image feature information extraction, is replaced by the MobileNetv3 network to realize the recognition of abnormal conditions such as empty aspiration, air bubbles and blockage during pipetting;then the U-Net network model is built to integrate the CBAM attention mechanism module and the residual module to realize the segmentation of pipetting areas. Then, we construct a U-Net network model incorporating the CBAM attention mechanism module and residual module to segment the pipetting area. The results showed that the model size of the improved YOLOv3 network was reduced by 139.1 MB and the frame rate per second (FPS) was increased by 15.7 frames/s. The improved U-Net network improved the IOU and F1 values for pipetting area segmentation by 8% and 13% respectively. © 2023 IEEE.

关键词： Process monitoring

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control law design for localizer pre-capture based on integrated navigation 2

Control law design for localizer pre-capture based on integr...

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2nd International Symposium on Aerospace engineering and Systems, ISAES 2023

作者： Zhang, Jiahao Meng, Fandong Zhou, Chao Gao, Zhiyuan School of Mechatronic Engineering and Automation Shanghai University Shanghai China Comac Aircraft Electronics Electrical and Control Integration Division Shanghai China

ISBN: (纸本)9798350303728

To enhance the performance of automatic landing systems for commercial aircraft, a control law of localizer pre-capture was developed based on the maximum pitch angle limit of the approach, the characteristics of the aircraft and localizer, and the fusion signals of the integrated navigation are used to delineate the approach paths and adjust the intercept angle. The modeling and simulation of the control law was implemented using MATLAB/Simulink. The simulation results show that the designed control law can guide the aircraft into the linear beam range of the localizer with appropriate intercept angle in various complex situations. The proposed method can provide a reference for further research of automatic flight control system for commercial aircraft. © 2023 IEEE.

关键词： Air navigation

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