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Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating with Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional method suffers from poor position and speed estimation accuracy under dynamic conditions, and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this paper. Differing from conventional method, a reduced-order linear state equation encompassing rotor position, speed and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process, but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameters variations. Additionally, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy.1 © 1986-2012 IEEE.

关键词： Permanent magnets

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Modified multi-scale symbolic dynamic entropy and fuzzy broad learning-based fast fault diagnosis of railway point machines

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Transportation Safety and Environment 2023年第4期5卷 1-7页

作者： Junqi Liu Tao Wen Guo Xie Yuan Cao Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048ShaanxiChina School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation Control System Beijing Jiaotong UniversityBeijing 100044China

Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident *** realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy ***,the fuzzy BLS takes the above entropy features as input to complete model *** BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational *** results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.

关键词： railway point machine(RPM) fault diagnosis modified multi-scale symbolic dynamic entropy(MMSDE) fuzzy board learning system(BLS)

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Study of multilevel feature weighted fusion based image classification method for silicon single crystal growth process

Study of multilevel feature weighted fusion based image clas...

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2024 International Conference on Image processing and Artificial Intelligence, ICIPAl 2024

作者： Xie, Ruidong Zhang, Zheqi Zhu, Pei Ma, Wenle Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510681514

A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification. © 2024 SPIE.

关键词： Image classification

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Improved Kalman Filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process 7

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Xie, Ruidong Zhu, Pei Ma, Wenle Zhang, Zheqi Yi, Yingmin Guo, Zheng Xi'an University of Technology Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an710048 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9798350363173

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors. © 2024 IEEE.

关键词： Kalman filters

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Cognitive Navigation for intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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EPM-Net: A better way for optical and infrared scene matching via edge point 12

EPM-Net: A better way for optical and infrared scene matchin...

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SPIE 12th International Symposium on Multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Huang, Shixiang Chi, Longyun Fu, Wenxing Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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A semantic segmentation method for UAV image based on improved BiseNetv2 5

A semantic segmentation method for UAV image based on improv...

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5th International Conference on Artificial Intelligence and Computer Science, AICS 2023

作者： Guo, Fengjuan Han, Sen Zhao, Jiahang Han, Jiale Xin, Jing Shaanxi Key Laboratory of Integrated and Intelligent Navigation The 20th Research Institute of China Electronics Technology Corporation Shaanxi Xi’an710068 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Shaanxi Xi’an710048 China

ISBN: (纸本)9781510668621

Aiming at the problem of low semantic segmentation accuracy of tiny targets in UAV aerial images, a bilateral semantic segmentation network T-BiseNetv2 is proposed. The proposed segmentation network is based on BiseNetv2, and the Transformer structure is introduced into semantic branch, and the detail branch and feature fusion module are reconstructed, which improves the network’s capacity to capture both global context information and local semantic information. Several semantic segmentation experiments are conducted on the standard semantic segmentation dataset UAVID, experimental results show that the proposed semantic segmentation network T-BiseNetv2 has a MIoU of 69.52%, which is about 2.2% higher than the original BiseNetv2 network. Especially, for "Human", the IoU of TBiseNetv2 is about 4.3% higher than that of the popular UNetFormer. © 2023 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation

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Chinese Journal of Electronics 2023年第1期32卷 189-198页

作者： GUAN Qi SHENG Zihao XUE Shibei Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Real-time six degrees-of-freedom(6D)object pose estimation is essential for many real-world applications, such as robotic grasping and augmented reality. To achieve an accurate object pose estimation from RGB images in real-time, we propose an effective and lightweight model, namely high-resolution 6D pose estimation network(HRPose). We adopt the efficient and small HRNetV2-W18 as a feature extractor to reduce computational burdens while generating accurate 6D poses. With only 33% of the model size and lower computational costs, our HRPose achieves comparable performance compared with state-of-the-art models. Moreover, by transferring knowledge from a large model to our proposed HRPose through output and feature-similarity distillations, the performance of our HRPose is improved in effectiveness and efficiency. Numerical experiments on the widely-used benchmark LINEMOD demonstrate the superiority of our proposed HRPose against state-of-the-art methods.

关键词： Knowledge engineering Computational modeling Pose estimation Grasping Benchmark testing Feature extraction Real-time systems

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Integrated design and performance optimization of three-electrode sliding discharge plasma power supply

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Plasma Science and Technology 2024年第11期26卷 152-161页

作者： Borui ZHENG Linwu WANG Jianbo ZHANG Shaojie QI Yuhong CHEN Haodong LIU Dongliang BIAN School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048People’s Republic of China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038People’s Republic of China

The three-electrode sliding dielectric barrier discharge(TES-DBD) plasma actuator significantly enhances the ionization rate and momentum exchange between charged particles and neutral particles by incorporating a parallel DC electrode into the standard DBD design. This design improves the body force and induced jet velocity while allowing flexible control of the induced jet angle, overcoming the limitations of discharge extension and uncontrollable direction in traditional DBD plasma actuators. An integrated plasma power supply has been designed specifically for TES-DBD plasma actuators, streamlining the power supply management. The methodology involves designing the circuit topology for the TES-DBD power supply, followed by simulating and validating its operating principles using Multisim software. The operational performance of the power supply is evaluated through a comprehensive analysis of its electrical,thermal, and aerodynamic properties specific to TES-DBD plasma actuation.

关键词： plasma flow control dielectric barrier discharge three-electrode sliding discharge plasma power supply

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Spatiotemporal evolution laws of sector-shaped dielectric-barrier-discharge plasma actuator

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Plasma Science and Technology 2024年第10期26卷 108-115页

作者： Borui ZHENG Jianbo ZHANG Shaojie QI Jianghua XU Yiche LI Yuanzhong JIN Dongliang BIAN School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048People’s Republic of China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038People’s Republic of China

Dielectric barrier discharge(DBD)plasma actuators are widely used in active flow control due to their simple design and rapid ***,they need more effectiveness and discharge *** overcome these limitations,a sector-shaped dielectric barrier discharge(SS-DBD)plasma actuator with an adjustable jet angle was developed to enhance flow control *** flow field dynamics induced by the SS-DBD plasma actuator were quantitatively analyzed using particle image velocimetry(PIV).Experimental investigations showed that precise adjustments to the actuation voltage can modulate the maximum velocity of the induced ***,a quasi-linear relationship between the sector-shaped angles of the SS-DBD and the deflected jet angles was established,indicating that changes in the sector-shaped angles directly influence the direction of the deflected *** correlation enables precise control over jet angles,significantly enhancing flow control by adjusting the SS-DBD-PA's sector-shaped angle.

关键词： plasma flow control plasma actuator particle image velocimetry

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