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High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain

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Chinese Journal of Aeronautics 2021年第5期34卷 652-665页

作者： Kang XU Shoukun WANG Junzheng WANG Xiuwen WANG Zhihua CHEN Jinge SI School of Automation Beijing Institute of Technology.Beijing 100081China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China Key Laboratory Ministry of Industry and Information Technology Beijing Institute of TechnologyBeijing 100081China

There is a strong demand for Planetary Exploration Mobile robots(PEMRs)that have the capability of the traversability,stability,efficiency and high load while tackling the specialized tasks on planet *** this paper,an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is ***,the hybrid control framework,which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion,is also *** on this framework,robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator(GG).Additionally,by using Whole-Body control(WBC)of framework,robot has the capability of flexibly accommodating the uneven terrain by Attitude control(AC)kinematically adjusting the length of legs like an active suspension system,and by Force/torque Balance control(FBC)equally distributing the Ground Reaction Force(GRF)to maintain a stable *** simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog ***,to smoothly demonstrate the performance of robot transporting heavy loads,the experiment of carrying 3-person load of about 240 kg is deployed.

关键词： Attitude control Gait generation High-adaption locomotion Obstacle avoidance Planetary exploration robot

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Coordinated Motion control for a Six-wheel-drive Skid-steering Mobile Robot

Coordinated Motion Control for a Six-wheel-drive Skid-steeri...

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2021 China Automation Congress, CAC 2021

作者： Xu, Yongkang Wang, Shoukun Zhao, Hongqiang Chen, Zhihua State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China State Key Laboratory of High Performance and Complex Manufacturing Central South University Changsha China

ISBN: (纸本)9781665426473

A speed consensus control strategy for a six-wheel-drive skid-steering mobile robot was proposed based on a hierarchical controller in a complex environment with unknown disturbances. The effective method of reliable speed consensus control strategy should consider some disturbances, such as the internal-robot assembly error, which including instability of motor control system and external physical interference in robot dynamic system. In this paper, a driving anti-slip control system with PID and the stability control system with sliding mode by variable structure is designed and integrated to elevate the stability of the robot. And, a G-vector control algorithm based on sliding mode control is proposed to reduce the yaw angle as much as possible during the process of differential steering of robots. The effectiveness of the proposed control strategy is verified by an example of a *** results show that the method has good control performance in control accuracy and stability. © 2021 IEEE

关键词： Motion control

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Two-Phase Hybrid Fuzzy Clustering Approach Using Membership Fusion

Two-Phase Hybrid Fuzzy Clustering Approach Using Membership ...

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第34届中国控制与决策会议

作者： Tian Gao Qinglin Wang Yaping Dai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to solve the problem that the clustering number in Fuzzy C-Means(FCM) needs to be set manually in advance,a two-phase hybrid fuzzy clustering approach using membership fusion(TPHFC) is *** the first phase,conventional FCM is used for *** the second phase,the results obtained by pre-clustering are fused according to the relationship between the membership of samples to different clusters and the membership threshold.A density-based clustering validity measurement is established for this *** proposed method obtains better clustering effect with setting fewer *** on synthetic datasets conforming to Gaussian distribution and UCI datasets demonstrate the effectiveness of the proposed clustering *** clustering number and clustering centers can be obtained adaptively.

关键词： Fuzzy Clustering Fuzzy C-Means Two-Stage Clustering Adaptive Parameter Adjustment

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Distributed Alternating Direction Method of Multipliers for Multi-Objective Optimization

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Advances in Pure Mathematics 2022年第4期12卷 249-259页

作者： Hui Deng Yangdong Xu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing China

In this paper, a distributed algorithm is proposed to solve a kind of multi-objective optimization problem based on the alternating direction method of multipliers. Compared with the centralized algorithms, this algorithm does not need a central node. Therefore, it has the characteristics of low communication burden and high privacy. In addition, numerical experiments are provided to validate the effectiveness of the proposed algorithm.

关键词： Alternating Direction Method of Multipliers Distributed Algorithm Multi-Objective Optimization Multi-Agent System

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Towards Pose Estimation for Large UAV in Close Range

Towards Pose Estimation for Large UAV in Close Range

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Ni Ou Junzheng Wang Shangfei Liu Jiehao Li State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665465373

This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.

关键词： Point cloud compression Measurement Cloud computing Pose estimation Vision sensors Autonomous aerial vehicles Laser modes

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Power System Events Classification Technology Based on Deep-Learning

Power System Events Classification Technology Based on Deep-...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Xin Lei Hongwei Ma Bin Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China College of Information Science and Engineering China University of Petroleum (Beijing) Beijing China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

As the complexity of the power system continues to increase, the frequency of the power system anomalies is on the rise. These anomalies have significant and widespread impacts on the stability of the power grid. Therefore, the rapid and accurate classification of these anomalies is crucial in preventing their further propagation and mitigating potential economic losses. This study presents an algorithm based on Phasor Measurement Unit (PMU) data for monitoring the state of power systems and identifying the types of anomalies. First, a dataset for anomaly event classification is created based on PMU data, which is used to train and validate the anomaly event classification model. Subsequently, a robust anomaly event classification model is constructed, consisting of a residual module with one-dimensional Convolutional Neural Networks (CNN) and a cascaded fully connected neural network classifier. This algorithm has undergone rigorous testing in the IEEE New England 39 bus test system, demonstrating exceptional event recognition accuracy.

关键词： Accuracy Power system stability Propagation losses Phasor measurement units Data models Stability analysis Classification algorithms

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Temperature control System of Thermoelectric Cooler Based on Improved ADRC

Temperature Control System of Thermoelectric Cooler Based on...

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第34届中国控制与决策会议

作者： Xiyuan Shan Tao Cai Zhicheng Zong Hongbo Mu School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Aiming at the problems containing complex working conditions,modeling difficulties and long-time delay of thermoelectric cooler temperature control system,an improved ADRC control method combining ADRC and Smith predictor is proposed in this *** deals with the disturbances and uncertain dynamics in the system,SP compensates the time delay to improve the control *** with the traditional PID controller,the proposed control method has faster response speed and stronger anti-disturbance ability,meanwhile,overcomes the dependence of Smith predictor on object parameters to a certain *** simulation and experimental verification,a good control effect is obtained,which provides a positive guidance of the related application of thermoelectric cooler.

关键词： Thermoelectric cooler(TEC) Active Disturbance Rejection control(ADRC) Smith Predictor(SP) Temperature control System

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An Improved Active Disturbance Rejection control Method for Crane System

An Improved Active Disturbance Rejection Control Method for ...

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第34届中国控制与决策会议

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to improve the dynamic performance of the underdriven crane system,an improved linear active disturbance rejection controller(LADRC) based on the new error was *** improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer(LESO).The improved method has two ***,the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances,which will limit the performance of the ***,the pole can be configured by adjusting the coefficient to obtain better dynamic ***,the effectiveness of the proposed method is verified by simulation and *** proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Crane LADRC New Error Underdriven System

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GAT-Net:A Network using Grid Attention and Transformer for Dynamic Facial Expression Recognition

GAT-Net:A Network using Grid Attention and Transformer for D...

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第34届中国控制与决策会议

作者： Wenxin Dai Yaping Dai Kaoru Hirota Shuai Shao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Dynamic facial expression recognition(DFER) in the wild has received widespread attention *** are complex factors such as face occlusion and pose variation in the *** expression recognition has a subtle competition between capturing local features of a human face and obtaining a global feature *** paper proposes an end-to-end DFER network GAT-Net based on the grid attention module and Transformer,which improves the robustness and accuracy of DFER in the ***,GAT-Net is divided into two components:spatial feature extraction and temporal feature *** grid attention module of the spatial feature extraction component guides the network to pay attention to the local salient features of the face,which reduces the interference of field occlusion and non-frontal *** Transformer in the temporal feature processing component guides the network to learn the temporal relationship of high-level semantic features and the global representation of facial expression *** two components balance the subtle competition between local features and global feature representations of facial *** ablation experiment has proved the effectiveness of the grid attention module and *** demonstrate that our GAT-Net outperforms state-of-the-art methods on DFEW and AFEW benchmarks with accuracies of 67.53%,and 50.14% respectively.

关键词： Facial Expression Recognition Deep Learning Attention Mechanism Transformer

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An Informer Based Alarm Early Prediction Method over Consecutive Alarm Monitoring Periods 22

An Informer Based Alarm Early Prediction Method over Consecu...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Jiang, Wenbin Hu, Wenkai Liu, Zhe Wang, Fei School of Automation China University of Geosciences Wuhan430074 China Petrochemical Company Limited Wuhan430082 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

ISBN: (纸本)9798331527471

Alarm systems serve as the first layer of protection for modern process industries to monitor industrial processes and ensure operational safety. However, the presence of alarm floods is common in alarm systems and may distract operators from critical alarms. To provide decision supports to operators during alarm flood situations, alarm prediction becomes a potential effective solution. The difficulty of alarm prediction lies in how to achieve high prediction accuracy over long-term consecutive alarm monitoring periods, including situations with either high or low alarm rates. Consequently, this paper presents an industrial alarm prediction method for both alarm flood periods and non-alarm flood periods. Specifically, a strategy of combining fixed-length and fixed-time sliding windows is designed. Further, an alarm prediction model based on Informer is proposed for alarm prediction under different alarm rates. A case study is presented to prove the validity of the proposed alarm prediction method. © 2024 IEEE.

关键词： Alarm systems

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