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15th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2023

作者： Wu, Weijun Guo, Zai-Cheng Zhu, Lei Nanjing Normal University School of Electrical and Automation Engineering Nanjing210046 China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering 999078 China

ISBN: (纸本)9798350338874

A new configuration is proposed for filters with parallel coupling paths between the source and load in this paper. The proposed fourth-order waveguide bandpass filter (BPF) with two parallel coupled paths is formally designed through this structure. The filter is working at 6.5 GHz and with 300 MHz bandwidth. Due to the two parallel coupling paths, a pair of transmission zeros (TZs) are generated out of passband. Compared with previous waveguide filters, the coupling paths are connected to the source and load in different sides of input/output waveguide. In this way, the waveguide cavity of the resonator can be increased and the insertion loss of the filter can be greatly reduced. The effectiveness of the fourth-order waveguide bandpass filter is verified by simulation results. © 2023 IEEE.

关键词： Bandpass filters

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Design of Composite Two-Channel Disturbance Estimation Adaptive controller for Backlash-Like Hysteretic Nonlinear Systems

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Journal of Shanghai Jiaotong University (Science) 2025年 1-11页

作者： Liu, Qunpo Li, Jiakun Fei, Shumin Bu, Xuhui Naohiko, Hanajima School of Electrical Engineering and Automation Henan Polytechnic University Henan Jiaozuo454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment Henan Jiaozuo454003 China School of Automation Southeast University Nanjing210096 China College of Information and Systems Muroran Institute of Technology Hokkaido Muroran050-8585 Japan

For nonlinear systems with backlash-like hysteresis characteristics and external disturbance, a composite two-channel disturbance estimation adaptive controller is proposed to improve the trajectory tracking accuracy of the system. The unmodeled hysteresis and external disturbances are treated as lumped uncertainties, which are approximated by radial basis neural network and disturbance estimator respectively. These approximations are then linearly fused to form the compensation term for the lumped uncertainty. The second order linear filter is employed to estimate multiple differential terms, which are integrated into the controller design and dynamic system state updates, thereby reducing computational complexity. A weighted fusion mechanism is implemented for the two channels, and the adaptive update rate for each channel is determined based on the deviation between the lumped uncertainty reference value and the output of each channel. To address the challenges posed by the discontinuity of deviation and maintain system stability, the first-order low-pass filter is applied to smooth the deviation, enhancing system robustness. A trajectory tracking simulation of a single-input single-output nonlinear system is conducted to compare the performance of the proposed controller with baseline controllers, demonstrating the effectiveness of the composite two-channel disturbance estimation adaptive controller. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Self tuning control systems

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A Deep Deterministic Policy Gradient Algorithm Based controller with Adjustable Learning Rate for DC-AC Inverters 2

A Deep Deterministic Policy Gradient Algorithm Based Control...

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

作者： Ye, Jian Mei, Sen Guo, Huanyu Zhao, Di Zhang, Xinan School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Electrical Electronic and Computer Engineering University of Western Australia Perth Australia

ISBN: (纸本)9798350313765

This paper proposes an inverter control algorithm based on the deep deterministic policy gradient (DDPG) with adjustable learning rates. This algorithm retains the advantages of model-free control of the inverter and solves the inherent problem of learning rate setting in deep neural networks. As a result, the control algorithm can quickly converge to the desired state during training, accelerate the training process, and not be affected by the control effect. Through simulation, the training results of the adjustable learning rate DDPG algorithm are compared with those of the constant small learning rate and constant large learning rate DDPG algorithms. The simulation results show that the training efficiency is improved by 75%, while the control effect on the inverter is almost unaffected. © 2023 IEEE.

关键词： deep deterministic policy gradient algorithm learning rate reinforcement learning Three-Phase DC-AC Inverters

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Graph Attention Transformer with Dilated Causal Convolution and Laplacian Eigenvectors for Long-term Water Quality Prediction

Graph Attention Transformer with Dilated Causal Convolution ...

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

作者： Bi, Jing Chen, Danqing Yuan, Haitao College of Computer Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

Water quality prediction has emerged as a prominent research problem in recent years, which entails a spatiotemporal prediction task. However, several challenges are associated with water quality prediction: 1) water quality time series exhibit complex nonlinear relationships, making prediction challenging;2) water quality sensors are distributed across river networks, leading to strong spatial dependencies in water quality prediction;3) current methods like traditional machine learning methods have poor accuracy in long-term water quality prediction. To solve these problems, this work proposes a spatiotemporal prediction model named Graph Attention Transformer with Dilated Causal Convolution and Laplacian Eigenvectors (GTDL). First, dilated causal convolution is adopted to extract temporal features of input sequences. Second, a transformer with Laplacian eigenvectors is designed to extract spatial dependencies of river networks. Third, residual connections are utilized at the output stage to enhance the accuracy of the long-term prediction. Finally, GTDL is evaluated with two real-world water quality datasets and experimental results prove that GTDL outperforms other baseline methods regarding the prediction accuracy. Specifically, compared with five state-of-the-art prediction models, GTDL improves the prediction accuracy by 11.3%-63.5% and 6%-52.4% on two datasets, respectively. © 2024 IEEE.

关键词： Prediction models

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A Novel Multimodal Humanoid Robot control System Framework Design Based on SSVEP-BCI and Eye-Tracking 7

A Novel Multimodal Humanoid Robot Control System Framework D...

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7th International Conference on Biological Information and Biomedical engineering, BIBE 2024

作者： Han, Chunxiao Hu, Yue Liu, Yanli Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9783800762910

As population ageing increases, Brain-computer Interface (BCI) technology combined with humanoid robots has become an innovative solution to alleviate the stress of elderly care. To improve the reliability and stability of the BCI system in practical applications, this paper proposed a novel multimodal humanoid robot control system. There are two different control modalities in parallel: Steady State Visual Evoked Potential (SSVEP)-BCI control modality and Eye Tracking control modality. The system utilized blinks events enable the user to initiate the human-machine interface (HMI) autonomously, selected one of the control modes based on the user's attention state, and sent control commands to the robot for execution. This multimodal framework effectively solves the false triggering problem of the humanoid BCI system, and the humanoid robot can perform tasks more flexibly. © VDE VERLAG GMBH.

关键词： Anthropomorphic robots

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Enhanced Potato Detection Using an Improved YOLOv8 Algorithm 24

Enhanced Potato Detection Using an Improved YOLOv8 Algorithm

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9th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2024

作者： Wang, Zihan Zhang, Yunxi Ma, Yuqi Zhao, Ya Liu, Jia School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798400716911

This paper proposes a novel potato detection algorithm YOLOv8-P, based upon the improved YOLOv8 framework to achieve enhanced detection accuracy. The algorithm incorporates the BiFormer attention mechanism and introduces an additional detection layer specifically designed for large targets, thereby significantly improving the model's performance in identifying larger potatoes. Additionally, a comprehensive dataset named potato-2024 was developed to address the limitations of existing public datasets in potato detection. To validate the effectiveness of YOLOv8-P, comparative experiments were conducted with YOLOv5 and YOLOv8 on the potato-2024 dataset. The results demonstrate that, under identical experimental conditions and parameters, YOLOv8-P exhibits superior recognition accuracy in potato identification, thus establishing a new benchmark in potato detection technology. © 2024 Copyright held by the owner/author(s).

关键词： YOLOv8

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Fall Detection System Based on YOLO Algorithm and MobileNetV2 Model 10

Fall Detection System Based on YOLO Algorithm and MobileNetV...

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10th International Conference on Systems and Informatics, ICSAI 2024

作者： Han, Chunxiao Zhang, Jingyan Wu, Han Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9798331510138

Accidental falls are the major causes of injury among elderly people living alone. However, traditional fall detection algorithms usually have missed or false detections problems. In this paper, we design a fall detection system based on YOLO algorithm and MobileNetV2 model. First, detection frame coordinates and joint coordinates of the human body are fused as feature information, and background information is filtered out. A lightweight deep learning model, MobileNetV2, is then used for classification. Compared with commonly used lightweight classification models such as ShuffleNet and EfficientNet, the MobileNetV2 model performs better in recognizing fall behavior. Our system can effectively distinguish fall behavior from daily activities, meeting the requirements for fall detection. © 2024 IEEE.

关键词： Fall detection

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A Binocular Vision-Based Method for Volume Measurement of Colloids

A Binocular Vision-Based Method for Volume Measurement of Co...

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2024 China automation Congress, CAC 2024

作者： Liao, Binrong Li, Yuxuan Zhang, Hao Zhu, Cong Yang, Yongkuan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China

ISBN: (纸本)9798350368604

Traditional binocular vision matching methods struggle to correctly match left and right colloid images due to the high reflectivity and textureless characteristics of colloid material surfaces, making effective volume detection difficult. To address this issue, we propose a binocular vision-based method for detecting the volume of dot-shaped colloids. First, to overcome the challenge of image edge extraction caused by specular reflection on colloid surfaces, we introduce an improved method for detecting and removing specular reflections. This method effectively detects and eliminates specular highlights on the colloid surface while restoring the surface color information, thereby enhancing edge detection accuracy. Next, we acquire the morphological characteristics of colloids from two perspectives (top view and side view) using binocular vision. Finally, we construct a mathematical model of the colloid volume based on its morphological characteristics and use a scale conversion factor to calculate the colloid volume. Experimental results show that the error precision of this volume measurement method is 4.52%, meeting the requirements of industrial production. © 2024 IEEE.

关键词： Binocular vision

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Research and Design of New Energy Dry-Type Transformer Prediction Device 2

Research and Design of New Energy Dry-Type Transformer Predi...

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2nd IEEE International Conference on Sensors, Electronics and computer engineering, ICSECE 2024

作者： Lin, Zhangzheng Sang, Zhongqing Feng, Nairu He, Zewen School of Electrical Engineering and Automation Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China

ISBN: (纸本)9798350373646

The main problem in dry-type transformers for new energy applications is the frequent temperature changes, which can reach temperatures of up to 180°C in actual operation. Due to the different expansion coefficients between epoxy resin and copper rows in dry-type transformers, the sealing of epoxy resin will be destroyed, leading to serious consequences such as dry-type transformer fire and explosion. For this reason, this paper designs a new energy dry-type transformer prediction device for transformer temperature and partial discharge signal monitoring and fault alarm, and studies the application of high-frequency current transformer (HFCT) in partial discharge monitoring to achieve real-time monitoring of transformer operation status. Finite element simulation software was used to analyze a dry-type transformer's simulation model. The simulation data obtained were then verified through real experimental testing. In the real grid system, simulations were conducted to model turn-to-turn short-circuit faults. The aim was to validate the simulation results and determine the required monitoring devices. The effectiveness of different monitoring methods-HFCT (High-Frequency Current Transformer), ultrasonic, ultra-high-frequency (UHF), and ground wave detection-was compared. It was found that HFCT is more effective than the other three methods in monitoring dry-type transformers. © 2024 IEEE.

关键词： Partial discharges

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Low-Cost Real-World Benchmark Framework for Closed-Loop Robot Navigation Systems with SLAM

Low-Cost Real-World Benchmark Framework for Closed-Loop Robo...

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2024 IEEE Opportunity Research Scholars Symposium, ORSS 2024

作者： Cort, Carlton Dalal, Aditya De Ocampo, James Du, Yanwei Feng, Shiyu Vela, Patricio A. Intelligent Vision and Automation Lab Georgia Tech Institute for Robots and Intelligent Machines Georgia Tech School of Electrical and Computer Engineering United States

ISBN: (纸本)9798350390698

Simultaneous localization and mapping (SLAM) and navigation systems are pivotal to realizing autonomous robotic capabilities. Research toward these systems will have direct impacts on the already large and rapidly growing market of autonomous robotics. Typically, research efforts in SLAM and navigation isolate one of the two systems when benchmarking their performance. As such, potential confounding issues from integrating the full navigation stack with pose estimates from a SLAM algorithm, such as the compounded latency of both systems, never arise. This paper aims to remove this shortcoming by providing a cost-effective closed-loop benchmarking framework for several navigation stacks integrated with several SLAM algorithms on a physical platform (Turtlebot2 in an office environment). A frugal vision-based motion capture method is utilized to capture the localization data. The lessened cost of such a system removes the barriers to real-world testing of this type often presented by common expensive motion capture systems. In the benchmarking framework, conventional performance metrics for both SLAM and navigation research and novel metrics were collected to characterize the closed-loop performance. An analysis of these metrics will enable the selection of algorithms for real-world applications since the framework tests complete mobile autonomy stacks in a task-driven closed-loop environment. © 2024 IEEE.

关键词： SLAM robotics

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