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2021 China automation Congress, CAC 2021

作者： Wang, Chen Jiao, Shangbin Gao, Rui Li, Yuxing School of Automation and Information Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China School of Electronic and Electrical Engineering Baoji University of Arts and Sciences Baoji China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Baoji China

ISBN: (纸本)9781665426473

To address shortcomings of ICP algorithm, which is sensitive to the initial position and easy to fall into local optimum, we propose a Harris Hawks Optimizer (HHO) point cloud registration method combining PCA preprocessing and parallel population initialization. The PCA method is used to align the point clouds with the main axes and perform the main axes correction. Since the six input variables in the population initialization stage of HHO point cloud registration are different and independent, the initial population of HHO algorithm is initialized by the parallel initialization method. The results show that the improved algorithm is able to successfully overwhelm the fault of ICP algorithm, and its global seek performance and optimization accuracy are more advantageous, and the algorithm operates efficiently, with high registration accuracy and robustness. © 2021 IEEE

关键词： PCA HHO Parallel Computing ICP

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Torque Compensation Model and Touchdown Detection Model of the Hydraulic Quadruped Robot controlled by VMC

Torque Compensation Model and Touchdown Detection Model of t...

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Chinese control and Decision Conference, CCDC

作者： Ranjiang Wang Jiangbo Zhao Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665478977

In this paper, according to the different dynamic models of the support phase and the swing phase, the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC). This compensation can increase the tracking effect of the foot end on the swing trajectory, reduce the elasticity and damping coefficient of the virtual model method, and increase the flexibility of the leg. Then this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the leg. At the end of this paper, simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.

关键词： Legged locomotion Damping Torque Switches Hydraulic systems Elasticity Mathematical models

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An Insulator Missing Defect Detection Method Based on Unmanned Aerial Vehicles

An Insulator Missing Defect Detection Method Based on Unmann...

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International Conference on control and automation (ICCA)

作者： Yulong Zhang Zhongxian Zhou Lingxia Mu Xianghong Xue Jing Xin Youmin Zhang School of Automation and Information Engineering Xi'an University of Technology Xi'an Shaanxi China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, an insulator missing defect detection method is proposed based on unmanned aerial vehicles to solve the problem of glass insulator burst fault detection in high-voltage transmission lines. Firstly, the proposed method utilizes the improved Mask R-CNN (region-based convolutional neural network) algorithm to segment insulator strings in aerial images. Then, the constructed encoder-decoder network is used to extract and reconstruct features of the insulators, resulting in residual images. Finally, the residual images preserve the location information of the fault and obtains the result of missing insulators. The experiment shows that the proposed algorithm has high segmentation accuracy for insulators and high recognition accuracy for insulator missing faults.

关键词： Image segmentation Accuracy Power transmission lines Fault detection High-voltage techniques Insulators Feature extraction

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The 110kV Live-Maintaining Robot control system Design for Substation Equipment in complex Working Conditions 42

The 110kV Live-Maintaining Robot Control System Design for S...

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42nd Chinese control Conference, CCC 2023

作者： Hu, Chenyu Chen, Xin Li, Chengyu Huang, Guangxian Zhou, Cheng Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Future Technology China University of Geosciences Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Distribution Department Xianning437000 China State Grid Hubei Electric Power Co. Ltd Operations and Maintenance Department Xianning xian'An District Power Supply Company Xianning437000 China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Live-maintaining work is essential for continuous power supply to the substation. To improve the safety and efficiency of live-maintaining work, this paper proposes an equipotential live-maintaining robot system suitable for 110kV voltage levels. Considering the narrow space, complex working conditions and strong electromagnetic interference in substations, binocular vision technology, manipulator trajectory planning algorithm based on time-energy optimization, high voltage electromagnetic shielding technology are utilized to develop the system, and the live-maintaining robot is successfully applied in actual substation. By accurately identifying and locating the joint bolts and insulator, the robot system can achieve equipotential live-disassemble, live-assemble the joint bolts within 18 minutes and live-clean insulator within 5 minutes, demonstrating its the effectiveness and practicability. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Electromagnetic pulse

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Geological Reservoir Modeling Method Based on Conditional Progressive Growing of GANs 26

Geological Reservoir Modeling Method Based on Conditional Pr...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Huang, Huaijin Liu, Xiaobo Zheng, Yiting Zhang, Dongsen Xiang, Hongbo School of Automation China University of Geosciences Wuhan430074 China China University of Geosciences Hubei Key Lab of Advanced Control and Intelligent Automation Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798331521950

Accurately characterizing geological patterns in reservoir modeling remains a significant challenge due to their inherent spatial heterogeneity and complexity. This paper proposes a Conditional Progressive Growing of GANs (CPGAN), which improves progressive growing of GANs (PGGAN) and Conditional GAN (CGAN). In this approach, the generator architecture of PGGAN is revised to incorporate a conditioning data input pipeline, allowing the generator to learn the features of geological patterns and conditioning data across different scales. In addition, a loss function derived from the conditioning data is introduced. This function defines the distance between the generated reservoir model and the conditioning data, guiding the generator in learning how the conditioning data constrain geological patterns. Experimental results indicate that CPGAN can generate high-quality reservoir models that comply with geological patterns and meet the constraints of the conditioning data. © 2025 IEEE.

关键词： Petroleum reservoir evaluation

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Learning to Find Good Correspondences Based on Global and Local Attention Mechanism

Learning to Find Good Correspondences Based on Global and Lo...

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2021 China automation Congress, CAC 2021

作者： Chen, Jun Gu, Yue Luo, Linbo School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (纸本)9781665426473

We are committed to designing a method for establishing a set of reliable correspondences between two images in this paper. Previous work proposes an outlier removal network based on global and local attention mechanism. It normalizes the feature map under the guidance of attention weight, as a result the robustness to outliers is improved and inliers are better preserved. However, element-wise multiplication of these two different attentions makes them unable to perform their original functions. In order to overcome this limitation, a network based on attention mechanism has been designed in our work. Firstly, global attention is employed to compute a global weight which can help normalization focus on inliers and reduce the influence of outliers on context information. Secondly, to extract channel information, we use local attention to learn a channel weight for each correspondence. Finally, the above structures and residual network modules are combined for correspondence establishment. Experimental results show that our method is better than other SOTA methods. © 2021 IEEE

关键词： Computer vision

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Fixed-/Preassigned-Time Anti-Synchronization of Chaotic Neural Networks

Fixed-/Preassigned-Time Anti-Synchronization of Chaotic Neur...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Haoyu Li Leimin Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781665402460

This paper investigates a unified controller to solve the fixed-time anti-synchronization (FTAS) and preassigned-time anti-synchronization (PTAS) problems for chaotic neural networks. Under our controller, chaotic neural network can realize anti-synchronization within the fixed or preassigned time which greatly expands the practical application range of the anti-synchronization. In addition, sufficient conditions and time estimation on FTAS and PTAS are derived. Finally, the feasibility of the control scheme is proved via a numerical simulation.

关键词： Sufficient conditions Neural networks Estimation Numerical simulation Synchronization Cybernetics

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Neural-LAFC: A Neural Learning Adaptive Flight controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels

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UAV Remote Sensing Image Stitching 15th

UAV Remote Sensing Image Stitching

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15th International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019

作者： Wu, Hui Chen, Jun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9783030324551

The majority of image stitching (include UAV remote sensing images stitching) models are homography matrix transformation function, which could effectively simulate the rigid transformation of 2D images in 3D coordinate system. In order to prevent the accumulation of alignment errors (drift) and the projection distortion in the multi-image stitching task, we proposes a novel UAV remote sensing image stitching access consisting of homography transformation and Helmert transformation. In the overlapping and non-overlapping region we utility homography transformation and Helmert transformation respectively. With proposed method the UAV remote sensing image stitching result has fewer alignment errors and less projection distortion. © Springer Nature Switzerland AG, 2020.

关键词： Remote sensing

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Harmonic Disturbance Suppression for High-Performance Nonlinear Repetitive-control systems

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IFAC-PapersOnLine 2023年第2期56卷 4545-4550页

作者： Shengnan Tian Kang-Zhi Liu Manli Zhang Chengda Lu Min Wu Jinhua She School of Automation China University of Geosciences Wuhan 430074 China. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Department of Electrical and Electronic Engineering Chiba University Chiba 263-8522 Japan School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

This study focuses on the performance design issue of nonlinear repetitive control (RC) systems subject to harmonic disturbances. First, a Takagi-Sugeno fuzzy model is used to describe a nonlinear plant. Then, a repetitive controller featuring a harmonic disturbance period is integrated with an EID estimator to form an RC-EID structure. The structure has a learning feature that gradually reduces the harmonic disturbance estimation error by self-learning. The linear inequality matrices guarantee the stability of nonlinear RC systems. A case study with two permanent magnet synchronous motors shows that the presented RC-EID estimator enhances the harmonic disturbance-suppression performance while compensating for the phase lag caused by the conventional EID filter.

关键词： Nonlinear repetitive control systems harmonic disturbance suppression equivalent input disturbance performance enhancement

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