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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multiphysical analysis and motor design optimization. This article proposes a new method for thermal steady state modeling and analysis based on transfer learning (TL), which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on TL is developed: the model is pretrained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then, the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R^{2} and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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Interpretation of ADRC in Q-Structure 6

Interpretation of ADRC in Q-Structure

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Xu, Jiapeng Chen, Xiang Tan, Ying Zhou, Kemin University of Windsor Department of Electrical and Computer Engineering Windsor Canada The University of Melbourne Department of Mechanical Engineering Melbourne Australia Center for Advanced Control and Smart Operations Nanjing University Suzhou China

ISBN: (纸本)9798350356618

This paper presents a control structure featuring an operator Q driven by the residual signal, which indicates the difference between the measurement output and the estimated output from an observer. The form of this observer is very general, as long as it can generate the estimated state or relevant information that will be incorporated into this control structure. The operator Q introduces an extra design freedom to address uncertainties, such that linear active disturbance rejection control (LADRC) can be interpreted as a special case in the Q-structure when a linear extended state observer is used. © 2024 IEEE.

关键词： Disturbance rejection

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Comparison of pulse rate variability from post-auricula and heart rate variability during different body states for healthy subjects

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Journal of Medical engineering and Technology 2023年第3期47卷 179-188页

作者： Qi, Yusheng Zhang, Aihua Ma, Yurun Chang, Tingting Xu, Jianwen College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou China College of Computer and Communication Lanzhou University of Technology Lanzhou China

Heart rate variability (HRV) extracted from the electrocardiogram (ECG) is an essential indicator for assessing the autonomic nervous system in clinical. Some scholars have studied the feasibility of pulse rate variability (PRV) instead of HRV. However, there is little qualitative research in different body states. In this paper, the photoplethysmography (PPG) of postauricular and finger and the ECG of fifteen subjects were synchronously collected for comparative analysis. The eleven experiments were designed according to the daily living state, including the stationary state, limb movement state, and facial movement state. The substitutability of nine variables was investigated in the time, frequency, and nonlinearity domain by Passing Bablok regression and Bland Altman analysis. The results showed that the PPG of the finger was destroyed in the limb movement state. There were six variables of postauricular PRV, which showed a positive linear relationship and good agreement (p > 0.05, ratio (Formula presented.) 0.2) with HRV in all experiments. Our study suggests that the postauricular PPG could retain the necessary information of the pulse signal under the limb movement state and facial movement state. Therefore, postauricular PPG could be a better substitute for HRV, daily PPG detection, and mobile health than finger PPG. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Photoplethysmography

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Experimental Study on Motion controller based on NN-ARX and ARMAX Actuator Identification for 3-DoF Delta Parallel Robot 11

Experimental Study on Motion Controller based on NN-ARX and ...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Jalali, Hasan Damavandi, Hossein Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Sadjad University Faculty of Computer Engineering and Information Technology Mashhad Iran University of Tehran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

Today, system identification plays a pivotal role in control science and offering a myriad of applications. This paper places its focus on the identification of actuator models within real-world delta robots for informing controller design. Two identification methods, namely NN-ARX and ARMAX, have been employed to extract the dynamic characteristics of the robot actuators, resulting in dynamic models of these integral components being derived. These dynamic models have been utilized in simulations for controller design, and due to the disparities in the identification models, distinct controllers have been realized. Subsequently, these controllers have been practically implemented on delta robots, and their performances have been subjected to a comprehensive comparative analysis. The results demonstrate that controllers integrating the identified actuator models outperformed those designed without the incorporation of the identification models. In practice, the implementation of controllers based on NN-ARX yielded the most favorable results among all the tested controllers. This research not only underscores the importance of accurate actuator models in control system design but also highlights the superior performance of neural network-based controllers in real-world robotic applications. In particular, the practical results of NN-ARX-based controllers were able to achieve significantly lower RMSE of 2.3562, 1.9531, and 2.1185 for the three motors, respectively, as opposed to the 4.1369, 3.0125, and 3.0363 achieved by the ARMAX-based controllers. © 2023 IEEE.

关键词： controllers

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Impact of Parametric Uncertainties on the Steady-State Performances of DFIG-Based WECS 10th

Impact of Parametric Uncertainties on the Steady-State Perfo...

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10th EAI International Conference on Advancements of Science and Technology, EAI ICAST 2022

作者： Ayenew, Endalew Biru, Getachew Mulatu, Asrat Berhanu, Milkias Electrical Power and Control Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa University Addis Ababa Ethiopia Center of Excellence for Sustainable Energy College of Electrical and Mechanical Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia

ISBN: (纸本)9783031411724

This chapter presents the study carried out to discover uncertain parameters in a model of a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) and to investigate their effects on WECS plant while harvesting energy from wind at varying speeds. This is carried out by analytically formulating the steady-state models of a DFIG-based WECS and computing the parameters of these models at different wind speeds that drive wind turbines at rotor speed from sub-synchronous to super-synchronous. The main uncertain parameters in this system are the mutual reactances between stator and rotor windings, and the reactance of rotor winding. These variations happen due to the varying wind speed. The effect of parametric uncertainties on the steady-state performances of DFIG-based WECS is examined. The results depicted that the steady-state performances of DFIG-based WECS are influenced by uncertain phenomena. Typically a 0.5% change in mutual reactances caused up to 10 kW change in the generator output power. Mainly, it causes instability in the performances of the DFIG-based WECS and slightly reduces overall efficiency at a higher value of the wind speed. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： DFIG-based WECS HAWT Performances of WECS Uncertain parameter

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Adaptive Active Fault-Tolerant Attitude control for Spacecraft with Adaptive Prescribed Performance 6

Adaptive Active Fault-Tolerant Attitude Control for Spacecra...

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Yang, Ze Yang, Baoqing Ji, Ruihang Ma, Jie Harbin Institute of Technology Control and Simulation Center Harbin China National University of Singapore Department of Electrical and Computer Engineering Singapore

ISBN: (纸本)9798350316155

For spacecraft attitude control affected by environmental disturbance, parameter uncertainty and actuator fault, a novel composite active fault-tolerant scheme, combining a strong tracking Cubature Kalman filter (STCKF) with adaptive prescribed performance control (APPC), is investigated in this paper. The proposed STCKF is capable of estimating lumped fault rapidly but accurately, and it is robust to model uncertainty. An adaptive finite-time prescribed performance function (APPF) whose boundaries can be flexibly adjusted in the case of actuator faults is proposed. Then an active fault tolerant controller is designed using nonsingular terminal sliding mode control (NTSMC) in conjunction with APPF. Simulation experiments and comparisons show that the proposed strategy exhibits better fault tolerance, lower conservatism and better steady-state performance. © 2023 IEEE.

关键词： Attitude control

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Mining Erasable Itemsets from a Product Database with Quantitative Components 24

Mining Erasable Itemsets from a Product Database with Quanti...

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11th Multidisciplinary International Social Networks Conference, MISNC 2024

作者： Hong, Tzung-Pei Chen, Da Huang, Wei-Ming Tsai, Yu-Chuan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-Sen University Taiwan Department of Computer Science and Engineering Department of Electrical and Control China Steel Inc. China Library and Information Center National University of Kaohsiung Taiwan

ISBN: (纸本)9798400717550

Erasable itemset mining is one of the most well-known methods in data mining for optimizing limited materials. After mining erasable itemsets, the manager can rearrange the production plan effectively. However, in real applications, traditional mining methods neglect some critical factors, such as costs or quantities of components forming a product. This thesis thus considers mining erasable itemsets from a product database with quantitative components. An erasable profit-based itemset mining (EPIM) algorithm is proposed to mine erasable itemsets with low profits by analyzing the relationships between products and components. In experiments, a synthetic dataset was used to compare the performance in execution speed and memory usage under various threshold settings. It can also be easily generalized to find erasable itemsets satisfying the other criteria with a quantitative product database. © 2024 ACM.

关键词： Mine safety

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Multi-Objective Complementary control

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IEEE Transactions on Automatic control 2024年第6期70卷 3556-3570页

作者： Xu, Jiapeng Chen, Xiang Tan, Ying Zhou, Kemin University of Windsor Department of Electrical and Computer Engineering 401 Sunset Avenue WindsorONN9B 3P4 Canada The University of Melbourne Department of Mechanical Engineering MelbourneVIC3010 Australia Nanjing University Center for Advanced Control and Smart Operations Jiangsu Suzhou215163 China

This paper proposes a novel multi-objective control framework for linear time-invariant systems in which performance and robustness can be achieved in a complementary way instead of a trade-off. In particular, a state-space solution is first established for a new stabilizing control structure consisting of two independently designed controllers coordinated with a Youla-type operator Q. It is then shown by performance analysis that these two independently designed controllers operate in a naturally complementary way for a tracking control system, due to the coordination function of Q driven by the residual signal of a Luenberger observer. Moreover, it is pointed out that Q could be further optimized with an additional gain factor to achieve improved performance, through a data-driven methodology for a measured cost function. © 1963-2012 IEEE.

关键词： Cost functions

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Research on traffic vehicle target detection method based on improved YOLOv7 24

Research on traffic vehicle target detection method based on...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Zhang, Feng Sun, Quan Yuan, Shuai School of Electrical and Control Engineering Shenyang Jianzhu University China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction Shenyang Branch of National Special Computer Engineering Technology Research Center China

ISBN: (纸本)9798400716720

With the increase in the number of vehicles in our country, traffic accidents have become frequent. The real-time detection of dense traffic vehicles is particularly important, which can promote the development of autonomous driving and lay a good foundation for intelligent transportation. Aiming at the problems such as high vehicle overlap rate, high small target missing rate and poor real-time detection in traffic vehicle data set, a traffic vehicle target detection method based on improved YOLOv7 was proposed. Firstly, the neck network structure of the original YOLOv7 is lightweight and introduced into the GhostSlimPAN paradigm structure to reduce the number of model parameters and operation cost, and improve the accuracy of detection of small target vehicles. Then, the original loss function CIoU is improved to replusion loss function to reduce the missed and false detection rate caused by mutual occlusion between vehicles. In order to verify the effect of the improved model, the vehicle dataset was selected for testing and verification. The experimental results show that compared with the original YOLOv7 algorithm, the mAP@0.5 of the improved YOLOv7 algorithm on this dataset reaches 88.2%, which is 1.8% higher than that of the benchmark network. The improved algorithm can be applied to vehicle target detection in daily environment, providing key technical support for intelligent transportation and autonomous driving. © 2024 ACM.

关键词： Autonomous vehicles

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Image Recognition of Concrete Electromagnetic Flaw Detection Based on Improved YOLOv7 24

Image Recognition of Concrete Electromagnetic Flaw Detection...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Yuan, Shuai Yuan, Ze He, Kai School of Computer Science and Engineering Shenyang Jianzhu University China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction China Shenyang Branch of National Special Computer Engineering Technology Research Center China School of Electrical and Control Engineering Shenyang Jianzhu University China

ISBN: (纸本)9798400716720

Owing to the invisibility characteristics of the interiors of concrete structures, nondestructive testing technologies are commonly employed to detect internal damage. Electromagnetic flaw detection technology, as a prominent nondestructive testing method, offers capabilities of strong penetration and precise imaging. However, the output images produced by this detection technology are usually reliant on subjective human judgment, and existing automatic detection algorithms have limitations in terms of accuracy. To enhance the accuracy of electromagnetic flaw detection images, this paper proposes improved YOLOv7 based detection method. First of all, the ACBlock convolution module is introduced to replace the original 3×3 convolution kernel for alleviating the loss of edge feature information caused by the sampling operation of the backbone network MP module. Next, in order to have more focus on the semantic features of small targets, a global attention mechanism (GAMAttention) is incorporated into the algorithm. Then, the FReLU activation function is adopted to enhance the algorithm sensitivity to image space. Finally, experiments are conducted on a self-created concrete flaw detection image dataset to illustrate the efficiency of the proposed algorithm. The results show that the mean Average Precision (mAP) value achieved by the improved algorithm is 95.85%. which has a significant improvement of 13.89% in comparison with the pre-improved YOLOv7 algorithm and surpasses other algorithms in the same domain. These findings represent that the proposed algorithm effectively enhances the accuracy of concrete electromagnetic flaw detection image detection. © 2024 ACM.

关键词： Nondestructive examination

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