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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Wang, Ziqi Yuan, Haitao Yang, Jinhong Zhang, Jia College of Computer Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Cssc Systems Engineering Research Institute Beijing China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9781665410205

Swarm intelligence and evolutionary algorithms are widely applied in industrial scheduling, mobile edge computing, etc due to their strong robustness and fast optimization speed. However, some real-world industrial optimization problems involve numerous decision variables, known as high-dimensional problems. Current algorithms often require considerable computational resources to evaluate objective function values because of high-dimensional decision spaces. Moreover, they are also prone to be trapped in local optima. To solve the above problems, this work proposes an improved algorithm named Surrogate-assisted Multi-class Collaborative Teaching and learning optimizer (SMCT). A multi-class collaborative teaching and learning optimizer is proposed as a base optimizer to improve exploration and exploitation abilities. Furthermore, an autoencoder-assisted radial basis function is proposed as the surrogate model to replace true function evaluations, thereby saving computational resources and balancing the complexity and accuracy in fitting true models. Finally, experimental results demonstrate that SMCT surpasses its existing peers in both search accuracy and convergence speed across eight high-dimensional benchmark functions. © 2024 IEEE.

关键词： Scheduling algorithms

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Classification of Bearing Faults by Approximation of Peak-To-Peak Amplitudes Distribution 2nd

Classification of Bearing Faults by Approximation of Peak-To...

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2nd NIELIT's International Conference on Communication, Electronics and Digital Technologies, NICEDT 2024

作者： Karimov, Timur I. Logunov, Oleg Y. Druzhina, Olga S. Kolev, Georgii Y. Kopets, EkaterinaE. Kaplun, Dmitrii I. Department of Computer-Aided Design St. Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Youth Research Institute St. Petersburg Electro technical University "LETI" Saint Petersburg Russia Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes St. Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9789819736034

To diagnosis the bearings faults in electric machines, the common approach is to acquire vibration signals from the machine-mounted accelerometers and process them by machine learning (ML) algorithms. Although many features can be extracted from signals to perform the classification, methods that require a minimum number of features are of interest to facilitate real-time processing. As a promising technique, we present an approach involving approximation of the vibration signals peak-to-peak amplitudes distribution with a Weibull model, where two parameters of the model are considered as features. The resulting accuracy of the proposed classifier reached 99.6%, which is superior to other considered features pairs from time and frequency domain. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Weibull distribution

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Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 388-399页

作者：刘增敏王申涛姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China JD Business Growth Department Beijing 100176China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle(UAV)platform,the object detection algorithm based on deep aggregation network and high-resolution fusion module is ***,a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking *** the problem of object association failure caused by UAV movement,image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking *** simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform,and effectively solve the problem of association failure caused by UAV movement.

关键词： moving unmanned aerial vehicle(UAV)platform small object feature extraction image registration multi-object tracking

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control-Oriented Model for Energy-Efficient Electric Vehicle

Control-Oriented Model for Energy-Efficient Electric Vehicle

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Zoltán Pusztai Tamás Luspay Ferenc Friedler Vehicle Industry Research Center Széchenyi István University Győr Hungary Systems and Control Laboratory - HUN-REN Computer and Automation Research Institute Budapest Hungary

ISBN: (数字)9798350379365

ISBN: (纸本)9798350379372

In this paper, a control-oriented Linear Parameter Varying (LPV) model of an energy efficient electric vehicle is proposed, designed for model-based control to minimize energy consumption. The control inputs of the model include the torque reference and the actual cornering radius. The LPV model assesses the impact of cornering on driving resistances and, consequently, on energy consumption, which represents a novel approach. Due to the driving characteristics and the model nonlinear dynamics of the vehicle, a velocity-linearization based method was applied to obtain the parameter-dependent form. The obtained LPV model was then validated by using logged driving data, showing a root mean square error (RMSE) of 0.4682 m/s compared to the measured speed profile, thereby confirming the model's accuracy. The proposed LPV model can be utilized to develop energy-efficient driving strategies, making it highly relevant for the design and operation of energy-efficient vehicles.

关键词： Energy consumption Torque Measurement uncertainty Electric vehicles Energy efficiency Data models Nonlinear dynamical systems Root mean square Informatics Machine intelligence

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GGIMN: Gravity Gradient Image Matching Network with Adaptive Adjoint Smoothing for AUV Navigation

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IEEE Transactions on Vehicular Technology 2025年

作者： Li, Tianjiao Wang, Bo Song, Bao Deng, Zhihong Fu, Mengyin Beijing Institute of Technology School of Automation Beijing100081 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin300382 China Beijing Institute of Technology Engineering Research Center of the Ministry of Education for Navigation Guidance and Control Technology School of Automation Beijing100081 China Nanjing University of Science and Technology Nanjing210014 China

Gravity gradient-aided navigation is a promising navigation method for autonomous underwater vehicle (AUV), in which matching algorithm is its key technology. Image matching algorithms have higher matching accuracy and information utilization than single point matching and sequence matching. However, the spatial domain image feature matching ability is weak in areas with insignificant feature changes due to the uneven feature distribution in the gravity gradient reference map. To break through this limitation and solve the problem of insufficient spatial domain image feature matching ability, we propose a gravity gradient image matching network (GGIMN) with adaptive adjoint smoothing for AUV navigation and positioning. First, a training set for GGIMN with equal numbers of positive and negative samples is constructed by preparing the gravity gradient reference map and fitting the gravity gradient measured map. Then, the feature extraction part of MatchNet is expanded to construct a deep learning network with five gravity gradient twin towers in parallel. Subsequently, an adaptive adjoint smoothing method that combines the idea of sequence matching is proposed to solve the problem of unsmooth matching trajectory and further improve the matching accuracy. Finally, the GGIMN is trained offline, and the gravity gradient map is matched and positioned online. The results of marine experiments show that the GGIMN has higher matching and positioning accuracy, and the average positioning error is reduced beyond 70% compared with onedimensional matching algorithms such as single-point iteration and sequence matching. © 1967-2012 IEEE.

关键词： Image matching

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Improved control of Grid-Connected Photovoltaic and Energy Storage System Based on Virtual Resistance 2

Improved Control of Grid-Connected Photovoltaic and Energy S...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Kang, Jiahua Dong, Wei Xu, Jinming Diao, Hanxu Lv, Zhenhua Xie, Shaojun College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing China State Grid Jiangsu Electric Power Co. LTD. Research Institute Nanjing China

ISBN: (纸本)9798350313765

In practical applications, the photovoltaic and energy storage (PV&ES) system can reduce grid-connected power fluctuations and help solve the problems caused by the large amount of distributed photovoltaic generation connected to the grid. However, the presence of non-ideal factors such as rich voltage harmonics and large grid impedance in the grid may lead to the destabilization of the PV&ES system, so analyzing the stability of the PV&ES system under complex grid is needed. The emphasis of this paper is on the modeling and stability analysis of the PV&ES system. The accurate model is established by using the harmonic linearization, and stability analysis under different grid impedances is carried out using impedance analysis. As proved, the PV&ES system has better stability under weak grid, but poor stability under strong grid with lower phase margin. Based on this, a virtual resistance-based method for improving the PV&ES system output impedance characteristics is proposed to achieve better stability under different grid impedance conditions. The validity and feasibility of the above analysis are confirmed through simulation of three-phase grid-connected inverters prototype. © 2023 IEEE.

关键词： frequency coupling impedance modeling photovoltaic and energy storage system (PV&ES) weak grid

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

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Single-channel ultrahigh frequency moisture meter with direct measurement of moisture content of bulk materials

Single-channel ultrahigh frequency moisture meter with direc...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Mirhalil A. Ismailov Nikola N. Nikolov Mariela Alexandrova Department "Automation and Control of Technology Process in Production" «Tashkent Institute of Irrigation and Agricultural Mechanization Engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

ISBN: (数字)9798350353907

ISBN: (纸本)9798350353914

The article discusses the theoretical foundations of the design of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. In accordance with the requirements of the methodology for selecting efficiency criteria, it is necessary to develop structural diagrams of measuring devices. For these purposes, the standard deviation of the random error is determined, characterizing the accuracy. It includes the main components: sensitivity error, zero error and additive component. Mathematical models of structures are constructed and the standard deviation of random errors, which are caused by certain parameters and additive fluctuations, is calculated. A single-parameter ultrahigh-frequency method for determining the moisture content is proposed. This method provides high accuracy of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. The measuring device can be used in the agricultural industry, where humidity is one of the important parameters, starting with harvesting and ending with the release of finished products.

关键词： Meters Additives Accuracy Sensitivity Moisture UHF measurements Mathematical models Frequency measurement Informatics Standards

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Keeping Eyes on the Road: Understanding Driver Attention and Its Role in Safe Driving 9

Keeping Eyes on the Road: Understanding Driver Attention and...

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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Fiani, Francesca Ponzi, Valerio Russo, Samuele Department of Computer Control and Management Engineering Sapienza University of Rome Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Psychology Sapienza University of Rome Roma00185 Italy

Monitoring the driver’s attention is an important task to maintain the driver’s safety. The estimation of the driver’s gaze direction can help us to evaluate if the drivers are not focusing their attention on the street. For an evaluation of this type, comparing the inside view and outside scenery of the vehicle is essential, therefore we decided to create a specific dataset for this task. In this work, we realize a machine-learning-oriented approach to driver’s attention evaluation using a coupled visual perception system. By analyzing the road and the driver’s gaze simultaneously it is possible to understand if the driver is looking at the traffic signs detected. We evaluate if a determined Region Of Interest (ROI) contains a road sign or not through YOLOv8. © 2023 Copyright for this paper by its authors.

关键词： Machine learning

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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 146-159页

作者： Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang Key Laboratory of Networked Control Systems Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Computing Wichita State UniversityWichita 67260 USA Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeTN 37996 USA Department of Automation Technology ABB Corporate Research SwedenVasteras 72178Sweden Department of Intelligent Systems Royal Institute of Technology(KTH)Stockholm 11428Sweden

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment ***,traditional calibrations suffer inaccuracy and *** address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying *** our method,the spatial relationship is geometrically correlated between the sensing units and robotic *** decoupled estimations on rotation and translation could reduce the coupled errors during the ***,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and *** calibration has been evaluated on our developed *** the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,*** comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

关键词： Calibration inertial measurement unit(IMU) monocular camera robotic arm spiral moving trajectory

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