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6th International Conference on Internet of Things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Dan, Qiuyue Cui, Delong Peng, Zhiping Li, Qirui He, Jieguang Qiu, JinBo Jilin Institute of Chemical Technology School of Information and Control Engineering Jilin China Guangdong University of Petrochemical Technology School of Electronic and Information Engineering Maoming China Jiangmen Polytechnic Jiangmen China Guangdong University of Petrochemical Technology School of Computer Maoming China

ISBN: (纸本)9798350386974

Knowledge Graph Embedding (KGE) is important to the value of the Knowledge Graph (KG) in its application field. Currently, neural network-based models achieve the most advanced performance. However, these models rarely consider the potential information between entities and relations in KGs, and also suffer from the problems of complex structure and high consumption of computing resources. In this paper, we propose the simple and efficient model PartDensE by using dense network, combining specific sharing layer and relational awareness layer. Specifically, our model learns all entities and relationships individually and can mine hidden features to enrich global information. Also, learn all the information based on each relation and be able to accurately establish associations between entities and relations. PartDensE can capture global and local features and displayed and hide information, retaining as much valuable information as possible. We evaluated PartDensE with 4 indicators across on two baseline datasets. Numerous experimental data prove the effectiveness of our model. © 2024 IEEE.

关键词： Knowledge graph

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FPC-BTB detection and positioning system based on optimized YOLOv5

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Biomimetic Intelligence & Robotics 2023年第4期3卷 56-66页

作者： Changyu Jing Tianyu Fu Fengming Li Ligang Jin Rui Song School of Control Science and Engineering Shandong UniversityJinan 250000China School of Information and Engineering Shandong Jianzhu UniversityJinan 250101China Shandong Industrial Technology Research Institute Jinan 250100China

With the aim of addressing the visual positioning problem of board-to-board(BTB)jacks during the automatic assembly of flexible printed circuit(FPC)in mobile phones,an FPC-BTB jack detection method based on the optimized You Only Look Once,version 5(YOLOv5)deep learning algorithm was proposed in this *** FPC-BTB jack real-time detection and positioning system was developed for the real-time target detection and pose output synchronization of the BTB *** that basis,a visual positioning experimental platform that integrated a UR5e manipulator arm and Hikvision industrial camera was built for BTB jack detection and positioning *** indicated by the experimental results,the developed FPC-BTB jack detection and positioning system for BTB target recognition and positioning achieved a success rate of 99.677%.Its average detection accuracy reached 99.341%,the average confidence of the detected target was 91%,the detection and positioning speed reached 31.25 frames per second,and the positioning deviation was less than 0.93 mm,which conforms to the practical application requirements of the FPC assembly process.

关键词： Detection and positioning systems Deep learning Small target detection Posture estimation Flexible printed circuit

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Synchronization of Measuring Devices for Forensic Crash Testing 5

Synchronization of Measuring Devices for Forensic Crash Test...

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5th IEEE International Conference on Communications, information, Electronic and Energy Systems, CIEES 2024

作者： Vestenicky, Peter Kolla, Eduard University of Žilina Faculty of Electrical Engineering and Information Technology Dept. of Control and Information Systems Žilina Slovakia University of Žilina Institute of Forensic Research and Education Žilina Slovakia

ISBN: (纸本)9798350352863

The measurement of the dynamic parameters of vehicle motion is usually carried out by measuring the velocity of motion, accelerations and angular velocities in all three axes. For research applications, e.g. the DAS-3 with microwave velocity sensor from Corrsys Datron GmbH (now part of the Kistler Group) and the PicDaq5 from Dr. Steffan Datentechnik GmbH are used for this purpose. If the movement of the vehicle also needs to be documented by video, these three measuring devices need to be synchronized in time, e.g. by light pulses for the video and electrical pulses for the speed and acceleration meters. This paper describes the technical solution of the synchronization device, triggered manually during driving tests or by a ribbon switch in the case of measurements during crash tests. © 2024 IEEE.

关键词： Microwave sensors

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Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

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Chinese Journal of Aeronautics 2022年第5期35卷 40-52页

作者： Quanbo GE Zhongcheng MA Jinglan LI Qinmin YANG Zhenyu LU Hong LI School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Institute of Systems Science and Control Engineering School of AutomationHangzhou Dianzi UniversityHangzhou 310018China State Key Laboratory of Industrial Control Technology and the College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044China Chinese Flight Test Establishment Xi’an 710089China

Mobile robots are often subject to multiplicative noise in the target tracking tasks,where the multiplicative measurement noise is correlated with additive measurement *** this paper,first,a correlation multiplicative measurement noise model is *** is able to more accurately represent the measurement error caused by the distance sensor dependence ***,the estimated performance mismatch problem of Cubature Kalman Filter(CKF)under multiplicative noise is *** improved Gaussian filter algorithm is introduced to help obtain the CKF algorithm with correlated multiplicative *** practice,the model parameters are unknown or inaccurate,especially the correlation of noise is difficult to obtain,which can lead to a decrease in filtering accuracy or even *** address this,an adaptive CKF algorithm is further provided to achieve reliable state estimation for the unknown noise correlation coefficient and thus the application of the CKF algorithm is ***,the estimated performance is analyzed theoretically,and the simulation study is conducted to validate the effectiveness of the proposed algorithm.

关键词： Adaptive CKF Correlated noise Estimation accuracy Multiplicative noise Performance analysis Target tracking

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Novel GNSS Anti-Spoofing Technique Using Antenna Array Processing 16

Novel GNSS Anti-Spoofing Technique Using Antenna Array Proce...

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16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023

作者： Zhao, Yuqing Shen, Feng Xu, Dingjie Meng, Zhen School of Instrument Science and Engineering Harbin Institute of Technology Harbin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798350327144

A novel antenna array-based spoofing defense scheme for the Global Navigation Satellite System (GNSS) is developed in this paper. The basis of the proposed approach is the spatial processing, which can be divided into two successive steps. In the first step, to identify and suppress the spoofing under the noise level, we build a cyclic correlation matrix to provide the direction of arrival (DOA) of the incoming signals. A robust adaptive beamforming process based on eigenspace projection is then designed to eliminate the spoofing in the second step. In particular, the proposed technique is capable of adaptively eliminating spoofing while providing protection to the desired navigation signals. By exploiting the digitised baseband signals, our framework avoids acquiring and tracking all arriving signals, reducing the receiver's computational load. The effectiveness of our anti-spoofing strategy is illustrated by the simulation experiments. © 2023 IEEE.

关键词： Global positioning system

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DeepHC: Efficient Generating Tests with High Coverage for Deep Neural Networks 23

DeepHC: Efficient Generating Tests with High Coverage for De...

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23rd IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023

作者： Teng, Junyuan Yu, Tingting Chen, Rui Gao, Dongdong Jia, Chunpeng Beijing Institute of Control Engineering Beijing China Beijing Sunwise Information Technology Ltd. Beijing China

ISBN: (纸本)9798350359398

As deep neural networks (DNNs) are increasingly used in the software of aerospace, aviation, and other safety-critical fields, ensuring their reliability and safety becomes paramount. Software testing is still the most critical means to ensure software quality. In order to guarantee the adequacy and effectiveness of testing, aerospace and other industrial areas usually require very high test case coverage. Despite considerable advances in structured coverage criteria and coverage-guided adversarial examples generation for DNNs, there is a lack of in-depth research on how to efficiently generate test inputs with high coverage, which is essential for software testing. In this paper, we propose DeepHC, a general framework combining fuzzing and gradient-based algorithms to achieve high coverage towards 6 most widely used coverage criteria. To explore test inputs with high coverage, DeepHC adopts a novel evaluation strategy for selecting inputs that can activate neurons more efficiently. We evaluate the effectiveness of DeepHC on 2 popular datasets and 3 DNN models with different complexities. The experimental results show that DeepHC outperforms the state-of-the-art method in enhancing coverage. © 2023 IEEE.

关键词： Deep neural networks

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Composite Output Feedback control of Underactuated Overhead Crane Subject to Constraints and Parameter Uncertainties 50

Composite Output Feedback Control of Underactuated Overhead ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Zhang, Shengzeng Liu, Xinggao Basin, Michael Zhu, Haiyue Mi, Xiaoxiao He, Xiongxiong Robotics Institute Ningbo University of Technology Ningbo China College of Control Science & Engineering Zhejiang University Hangzhou China Singapore Institute of Manufacturing Technology Agency for Science Technology & Research Singapore College of Information & Engineering Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665464543

This paper proposes a nonlinear feedback control for overhead cranes that offer satisfactory performance by taking advantages of only a composite output. Particularly, the construction of a barrier function keeps the composite output between predefined boundary values, which can enhance the safety of the system. Nonetheless, the controller with simple structure ensures the stabilization of the payload despite the presence of parametric uncertainties. To substantiate the stability proof, two analytical methodologies are employed: the Lyapunov technique and LaSalle’s invariance principle. The simulation evidences efficient positioning and oscillation elimination of the controller for various uncertain parameters, large initial errors and external disturbances, without tuning the gains of each term. © 2024 IEEE.

关键词： Lyapunov methods

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Online controller Tuning Method Using Fictitious Reference Iterative Tuning Based on Recursive Least-Squares Method for Quadrotor Flight control

Online Controller Tuning Method Using Fictitious Reference I...

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2023 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2023

作者： Sato, Ayumu Tanaka, Ryo Advanced Engineering School National Institute of Technology Kurume College Fukuoka Japan National Institute of Technology Kurume College Department of Control and Information Systems Engineering Fukuoka Japan

ISBN: (纸本)9798350323153

This paper proposes an online controller tuning method using fictitious reference iterative tuning (FRIT) design method based on recursive least-squares (RLS) method for quadrotor flight control. FRIT is a method of directly adjusting controller parameters such as PID gains using input/output data without using a mathematical model of the controlled object. This paper compares the performance of conventional discrete PID control with that of discrete PID control implementing RLS-FRIT by simulation. The results show that the proposed RLS-FRIT has better control performance than the conventional method. The robustness against disturbances was also found to be superior to that of the conventional method. © 2023 IEEE.

关键词： Fictitious Reference Iterative Tuning (FRIT) Recursive Least-Squares (RLS)

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Real-Time UAV Fault Detection and Classification Using Measurement Data from the PADRE Database

Real-Time UAV Fault Detection and Classification Using Measu...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Puchalski, Radoslaw Giernacki, Wojciech Ha, Quang Institute of Robotics and Machine Intelligence University of Technology Faculty of Control Robotics and Electrical Engineering of Poznan Poznan Poland School of Electrical and Data Engineering University of Technology Sydney Faculty of Engineering and Information Technology UltimoNSW2007 Australia

ISBN: (纸本)9798350312072

The growing number of applications for unmanned aerial vehicles operating in close proximity to humans calls for strict safety requirements. To ensure reliability and safety, fast and effective diagnosis of possible drone faults is needed. In this paper, a study on the detection of damage to the propellers of a multirotor using inertial sensors was conducted. Measurement data from the publicly available PADRE repository were used. Frequency features and raw measurement data applicability were tested. Two different approaches to data processing during fault detection and classification were tested. The first is to analyze the signals after collecting the entire set of data needed for treatment by the neural network. The second approach processes the data after every single acquisition of sensor measurements. The performance results and processing time of each solution are recorded for analysis. By effectively selecting parameters of the proposed approaches, the processing time and accuracy of UAV fault classification can be significantly improved, as verified over different classes of propeller defects. Early fault detection is essential for safe operations of multirotor drones. © 2024 IEEE.

关键词： Drones

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