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Chinese automation Congress (CAC)

作者： Tianhe Liu Xin Chen Chenyu Hu Xu Jian Shengzu Li Gang Wang 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 Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an “eye-on-hand” configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within $\pm 4\text{mm}$ , outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots.

关键词： Location awareness Visualization Power transmission lines Accuracy Image color analysis Lighting Distribution networks Grasping Wire Robots

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Modified weak-value-amplification technique for measuring a mirror's velocity based on the Vernier effect

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Physical Review A 2022年第1期105卷 013718-013718页

作者： Jing-Hui Huang Fei-Fan He Xue-Ying Duan Guang-Jun Wang Xiang-Yun Hu Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 430074 Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education 430074 Wuhan China School of Automation China University of Geosciences Lumo Road 388 430074 Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems 430074 Wuhan China

A modified weak-value-amplification (MWVA) technique to measure a mirror's velocity based on the Vernier effect is proposed. To demonstrate its enhanced sensitivity and higher signal-to-noise ratio (SNR), we use two cascaded Michelson interferometers with similar optical structures. One has a fixed mirror and acts as a fixed part of the Vernier scale, while the other, with a moving mirror, acts as a sliding part of the Vernier scale for velocity sensing. The envelope of the cascaded interferometers shifts much more than a single one with a certain enhancement factor, which is related to the free space range difference between them. In addition, we calculate the SNR based on the Fisher information with both the MWVA and traditional weak-value-amplification (TWVA) techniques. The results show that both the SNR and the sensitivity with our MWVA technique is greater than that of the TWVA technique within the range of our time measurement window. In particular, MWVA can present a viable and effective alternative to the TWVA technique out of the limit of resolution. Furthermore, by using the principles of the Vernier effect, it is applicable and convenient to improve the sensitivity and SNR in measuring other quantities with the TWVA technique.

关键词： Quantum measurements Quantum optics

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Yujian Zhou Jinhua She Feng Wang Makoto Iwasaki 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 Engineering Tokyo University of Technology Hachioji Tokyo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method.

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A Reinforcement Learning Approach for Robust Restoration of Generators in Power System

A Reinforcement Learning Approach for Robust Restoration of ...

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Chinese automation Congress (CAC)

作者： Huimiao Li Xiaozhou Yang Chao Zhai School of Automation China University of Geosciences Wuhan Campus Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Singapore-ETH Centre CREATE Campus Future Resilient Systems Singapore

In the past decades, cascading blackouts have caused serious damages to power systems and affected the normal operation of society, so it is crucial to quickly restore the damaged power system to normal state. In this paper, a reinforcement learning (RL) approach is developed to achieve the robust restoration of generators in power systems. Firstly, the performance recovery of damaged power system is modeled as markov decision process, and constraints such as line voltage and active power output of generators are considered. Secondly, a RL algorithm is proposed to search the optimal control strategy for generator units recovery. Based on the proposed restoration approach, Q-learning algorithm is employed to obtain the optimal strategy for power supply of generaors in power grids. Finally, numerical simulations are carried out on IEEE 9-bus system under different scenarios of external disturbances and certainties. The simulation results demonstrate the effectiveness and feasibility of the proposed approach.

关键词： Q-learning Power supplies Simulation Power system protection Generators Explosions Power systems

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Circular Formation Flight control for Unmanned Aerial Vehicles With Directed Network and External Disturbance

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 505-516页

作者： Yangyang Chen Rui Yu Ya Zhang Chenglin Liu School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Advanced Process Control for Light Industry Ministry of EducationInstitute of AutomationJiangnan UniversityWuxi 214122China

This paper proposes a new distributed formation flight protocol for unmanned aerial vehicles(UAVs)to perform coordinated circular tracking around a set of circles on a target *** from the previous results limited in bidirectional networks and disturbance-free motions,this paper handles the circular formation flight control problem with both directed network and spatiotemporal disturbance with the knowledge of its upper *** from the design of a common Lyapunov fiunction for bidirectional cases,we separately design the control for the circular tracking subsystem and the formation keeping subsystem with the circular tracking error as *** the whole control system is regarded as a cascade connection of these two subsystems,which is proved to be stable by input-tostate stability(ISS)*** the purpose of encountering the external disturbance,the backstepping technology is introduced to design the control inputs of each UAV pointing to North and Down along the special sphere(say,the circular tracking control algorithm)with the help of the switching ***,the distributed linear consensus protocol integrated with anther switching anti-interference item is developed to construct the control input of each UAV pointing to east along the special sphere(say,the formation keeping control law)for formation *** validity of the proposed control law is proved both in the rigorous theory and through numerical simulations.

关键词： Directed network external disturbance flight control unmanned aerial vehicles(UAVs)

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems 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 School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front.

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Differential Steering control for 6 × 6 Wheel-drive Mobile Robot 26

Differential Steering Control for 6 × 6 Wheel-drive Mobile ...

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26th International Conference on automation and Computing, ICAC 2021

作者： Zhao, Hongqiang Luo, Chao Xu, Yongkang Li, Jiehao Central South University State Key Laboratory of High Performance Complex Manufacturing School of Mechanical and Electrical Engineering ChangSha China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing China

ISBN: (纸本)9781860435577

The 6 × 6 Wheel-drive mobile robot is widely used in the field of special operations, and there is the phenomenon of slipping in the process of steering. To study the steering accuracy and stability of mobile robot, the dynamic model of 6 × 6 Wheel-drive Mobile Robot is established, and the sliding mode control strategy of differential steering based on mobile robot is proposed. Firstly, taking the torque of six wheels and the operator's direction control as input, the three-dimensional attitude and the relative position of the steering center of the mobile robot are obtained by using the position and attitude sensor, to determine the reference steering angle of the mobile robot. Secondly, considering the relationship between the position error and the velocity error, a recursive sliding surface is designed, and a neural network is introduced to approach the uncertain part of the mobile robot model. Then, a nonlinear gain function is applied to construct a dynamic surface control law. Finally, through the Trucksim/Simulink co-simulation model, the nonlinear gain recursive sliding mode dynamic surface adaptive control method for mobile robot trajectory tracking can improve the tracking speed and control precision, and the control force and torque are smooth and reasonable. The results show that the method is effective in improving the steering accuracy and stability of mobile robot. © 2021 Chinese automation and Computing Society in the UK-CACSUK.

关键词： Mobile robots

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Hierarchical Adaptive Tracking control for Mobile Robots With Multiple Constraints

Hierarchical Adaptive Tracking Control for Mobile Robots Wit...

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Chinese automation Congress (CAC)

作者： Chenghao Zhao Shiqi Zheng Haiming Li Haitao Jian Shihao Wang School of Automation China University of Geosciences Wuhan Campus Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems Wuhan China

ISBN: (纸本)9781665426480

This paper studies the mobile robots with multiple constraints based on path planning of A-star algorithm. A hierarchical adaptive control method is presented to handle multiple constaints. On the upper layer, a Astar path planning algorithm is designed. On the lower layer, a new controller is provided. Then, we design barrier Lyapunov function and adaptive RBF neural network control method to make sure that tracking error and velocity error converges to the specified set within a finite amount of time. Compared with other existing works, this system considers multiple consraints include tracking error, constraints velocity constraints and output saturation constraint, provides guarantee for the safe operation of the mobile robot. In addition, because of the unknown conditions on the ground, system also considers the impact of slipping. Computer simulation result demonstrates the effectiveness of control method. In the experimental verification, we use A-star algorithm to generate the appropriate path as the desired trajectory of the mobile robot. The experiment proved the stability of control method.

关键词： automation Computer simulation Neural networks Approximation algorithms Stability analysis Trajectory Planning

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AFPN Based YOLOX for Rotation Object Detection in Remote Sensing Image

AFPN Based YOLOX for Rotation Object Detection in Remote Sen...

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Chinese automation Congress (CAC)

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

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Rotation Object Detection in Remote Sensing Image is a big challenge, as it has different sizes and orientations. In this paper, we proposed an AFPN and YOLOX based Rotation Object Detection method, named AFPN-RYOLOX. In the AFPN-RYOLOX, an angle prediction branch added into the detection head of YOLOX and revised the loss function to incorporate Kullback-Leibler Divergence (KLD) loss firstly, which enhanced loss continuity and ensuring scale invariance. Then, the Asymptotic Feature Pyramid Network (AFPN) is integrated in the neck layer of YOLOX, which boosts the network's capability to extract features and decreases the number of model parameters through a dual-phase adaptive spatial fusion process. Through compare with other SOTA method, the proposed AFPN-RYOLOX achieved superior performances on DOTA and HRSC2016 datasets.

关键词： Adaptation models Head automation Noise Object detection Feature extraction Prediction algorithms Neck Sensors Remote sensing

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