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206 results on '"Wu, Gongping"'

9. Robust Cascaded Model-Free Tolerant Control With Parameters Mismatch Fault Diagnosis for PMSM Drive System

Author

Wu, Gongping, Xiao, Hu, Long, Zhuo, He, Jing, and Li, Zewen

Abstract

Since the parameters mismatch fault caused by the mismatch between motor parameters and model predictive controller parameters can seriously affect the performance of the drive system, it is necessary to investigate parameters mismatch fault diagnosis and tolerant control. In this study, a novel robust cascaded model-free tolerant control (RCM-FTC) method with parameters mismatch fault diagnosis is proposed for a permanent magnet synchronous motor (PMSM) drive system, which can effectively improve the control performance of stator flux and torque under parameters mismatch faults. The parameters mismatch fault sensitivity of the PMSM drive system is analyzed, and a novel ultralocal model is established under the parameters mismatch fault. The multivariable integral terminal sliding mode observer (MIT-SMO) with improved sliding mode reaching law is designed to diagnose parameters mismatch faults and identify operating states in the PMSM drive system. The robust cascaded speed loop and stator flux loop control strategy are proposed for parameters mismatch faults by utilizing the model-free sliding mode control algorithm, which can eliminate the impact of parameters mismatch faults on the PMSM drive system. The test results demonstrate the effectiveness of the proposed RCM-FTC method in significantly eliminating stator flux/torque ripple and improving fault tolerance capabilities in the case of parameters mismatch faults.

Published
2025
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10. Motor Diagnosis Based on 3-D Spherical Projected Point Cloud

Author

Long, Zhuo, Xu, Zhiyuan, Wu, Gongping, Deng, Feng, Sun, Meidi, Wang, Ming-Hao, Huang, Zhiwen, and Feng, Wenshan

Abstract

The frequent occurrence of motor faults has been a great disturbance to the development of production in various fields. Traditional fault diagnosis methods primarily use 1-D data or 2-D data. However, 3-D data hold significant promise for motor fault diagnosis due to its voluminous data and unique spatial information. This article aims to explore a motor fault diagnosis method leveraging 3-D data. Nonetheless, motor fault 3-D data exhibit the limitation of lacking geometric structure. To address this limitation, this article proposes a fault diagnosis method named SP-PointCNN. This method uses the proposed spherical projection (SP) method to mitigate the limitations present in the 3-D data of the motor. Meanwhile, a neural network based on PointCNN is constructed to enable the utilization of 3-D data in fault diagnosis. A series of experiments demonstrated the validity of the proposed method. After tested, the diagnosis accuracy of SP-PointCNN can reach 99.36%.

Published
2025
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17. Motor Fault Diagnosis Using Attention-Based Multisensor Feature Fusion.

Author

Miao, Zhuoyao, Feng, Wenshan, Long, Zhuo, Wu, Gongping, Deng, Le, Zhou, Xuan, and Xie, Liwei

Subjects
CAPSULE neural networks, FAULT diagnosis, SYMMETRIC domains, MULTISENSOR data fusion, DETECTORS, MULTICHANNEL communication
Abstract

In order to reduce the influence of environmental noise and different operating conditions on the accuracy of motor fault diagnosis, this paper proposes a capsule network method combining multi-channel signals and the efficient channel attention (ECA) mechanism, sampling the data from multiple sensors and visualizing the one-dimensional time-frequency domain as a two-dimensional symmetric dot pattern (SDP) image, then fusing the multi-channel image data and extracting the image using a capsule network combining the ECA attention mechanism features to match eight different fault types for fault classification. In order to guarantee the universality of the suggested model, data from Case Western Reserve University (CWRU) is used for validation. The suggested multi-channel signal fusion ECA attention capsule network (MSF-ECA-CapsNet) model fault identification accuracy may reach 99.21%, according to the experimental findings, which is higher than the traditional method. Meanwhile, the method of multi-sensor data fusion and the use of the ECA attention mechanism make the diagnosis accuracy much higher. [ABSTRACT FROM AUTHOR]

Published
2024
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29. The Research on Mechanism, Kinematics and Experiment of 220kv Double-Circuit Transmission Line Inspection Robot

Author

Li, Cheng, Wu, Gongping, Cao, Heng, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Xie, Ming, editor, Xiong, Youlun, editor, Xiong, Caihua, editor, Liu, Honghai, editor, and Hu, Zhencheng, editor

Published
2009
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31. Motion Planning of Non-collision Obstacles Overcoming for High-Voltage Power Transmission-Line Inspection Robot

Author

Wu, Gongping, Xiao, Xiaohui, Xiao, Hua, Dai, Jinchun, Huang, Zhenglie, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Xiong, Caihua, editor, Huang, Yongan, editor, Xiong, Youlun, editor, and Liu, Honghai, editor

Published
2008
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38. Adaptive Droop-based Hierarchical Optimal Voltage Control Scheme for VSC-HVDC Connected Offshore Wind Farm

Author

Huang, Sheng, Wu, Qiuwei, Liao, Wu, Wu, Gongping, Li, Xueping, Wei, Juan, Huang, Sheng, Wu, Qiuwei, Liao, Wu, Wu, Gongping, Li, Xueping, and Wei, Juan

Abstract

An adaptive droop-based hierarchical optimal voltage control (DHOVC) scheme is proposed for voltage-source converter high-voltage-direct-current (VSC-HVDC) connected offshore wind farms (WFs). The wind turbines (WTs) and WF side VSC (WFVSC) are coordinated to minimize the voltage deviations of buses inside the WF from the nominal voltage and mitigate reactive power (Var) fluctuations of WTs. The model predictive control (MPC) is used to improve the performance of the DHOVC scheme during a certain predictive horizon. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed to reduce the calculation burden of the central controller while improving the information privacy protection. During the predictive horizon, the WTs and WFVSC are coordinated to achieve the near global optimal performance without global information. A WF with 32 × 5MW WTs was used in the matlab/simulink to test the proposed DHOVC scheme.

Published
2021

39. Predictive Torque and Stator Flux Control for N*3-phase PMSM Drives with Parameter Robustness Improvement

Author

Wu, Gongping, Huang, Sheng, Wu, Qiuwei, Zhang, Changfan, Rong, Fei, Hu, Yashan, Wu, Gongping, Huang, Sheng, Wu, Qiuwei, Zhang, Changfan, Rong, Fei, and Hu, Yashan

Abstract

In this study, a novel predictive torque and stator flux control (PTSF) method is proposed for N-segment three-phase PMSM (N*3-phase PMSM), which can effectively eliminate the influence of parameter mismatch on stator flux and torque. The proposed PTSF method has two loops, stator flux loop and torque loop, both implemented with robust predictive control algorithm. First, the stator flux predictive controller with parameter robustness is designed, and the sensitivity of its parameters is analyzed. In the dq stator flux space, the robust stator flux predictive control with one-step delay compensation is then proposed, which can effectively enhance robustness against parameters mismatch. Moreover, the robust torque predictive control based on unknown torque disturbance observer is developed, which can effectively strengthen the robustness against the load torque disturbance and parameter mismatch. Finally, the validity and feasibility of proposed PTSF method are verified by simulation and experiment. Excellent simulation and experimental results were achieved with respect to the stator flux tracking error, torque /flux ripple reduction, and stator current distortion over conventional predictive torque control (PTC).

Published
2021

40. Robust Fault-Tolerant Predictive Current Control for Permanent Magnet Synchronous Motors Considering Demagnetization Fault

Author

Fei Rong, Feng Jianghua, Shoudao Huang, Wu Gongping, Jing He, Lin Jia, and Changfan Zhang

Subjects
Permanent magnet synchronous motor, Observer (quantum physics), Computer science, 020209 energy, 020208 electrical & electronic engineering, Demagnetizing field, Perturbation (astronomy), Fault tolerance, 02 engineering and technology, Control and Systems Engineering, Robustness (computer science), Control theory, Magnet, 0202 electrical engineering, electronic engineering, information engineering, State observer, Electrical and Electronic Engineering, Voltage
Abstract

In this study, a robust fault-tolerant predictive current control (RFT-PCC) algorithm based on a composite observer is proposed for permanent magnet synchronous motors (PMSMs), which can eliminate the influence of motor parameter perturbation and permanent magnet demagnetization. First, the effects of the parameter perturbation and permanent magnet demagnetization on the current vector are analyzed based on the conventional predictive current control. The composite observer based on the sliding mode observer and the Luenberger observer is then designed to observe the compensation voltage and current prediction value of the next time simultaneously. Finally, an RFT-PCC method is developed. The proposed RFT-PCC is able to effectively enhance robustness against parameter perturbation and permanent magnet demagnetization by adding compensation voltage. The current prediction value of the next time is used to replace the sampled current in RFT-PCC to compensate for the influence of the one-step delay. Comparative simulations and experimentations verify that the proposed RFT-PCC can improve the robustness while maintaining quick dynamic response of the current control loops.

Published
2018
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