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High-Precision Admittance control of Mechanical Arm Based on Force Sensor Compensation

High-Precision Admittance Control of Mechanical Arm Based on...

引用

第34届中国控制与决策会议

作者： Yaohui Wu Jiangbo Zhao Junzheng Wang Xin Zhang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd.

Admittance control is one of the important methods of compliance *** is performed by inputting force signals and outputting position *** control can achieve high accuracy,but the force signals have large errors,which is an important factor affecting its *** the force sensor collects force data,there are non-negligible initial deviations due to gravity,installation,and other factors,resulting in poor admittance control *** order to solve this problem,this paper takes the six-degree-of-freedom manipulator admittance control as the research *** to the mapping relationship between the end attitude and the sensor errors,we propose a method of obtaining the initial offset value of the sensor through data *** method traverses the initial values of the sensor in each working posture when the sensor has no external force input,and then performs secondary interpolation to obtain the offset values of the sensor in any posture,corrects the output values of the force/torque sensor,and then improve the accuracy of admittance *** experimental results show that this method can quickly and effectively improve the calculation accuracy of the sensor's initial deviation values and the admittance control accuracy.

关键词： Admittance control Force/torque sensor Quadratic interpolation Precision optimization

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Human Following Robot Based on Object Detection for Aerospace Application

Human Following Robot Based on Object Detection for Aerospac...

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Aerospace Electrical Engineering and Informatics (ICAAEEI), International Conference of Adisutjipto on

作者： Arwin Datumava Wahvudi Sumari Ahnaf Bagus Aryandika Ndaru Atmi Purnami Denny Dermawan Ika Noer Syamsiana Department of Electrical Engineering Cognitive Artificial Intelligence Research Group State Polytechnic of Malang Malang Indonesia Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Navigation Instrumentation Control Automation and Robotics System Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Digital System Microprocessor Microcontroller and Programmable Logic Devices Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia

ISBN: (数字)9798331507930

ISBN: (纸本)9798331507947

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications.

关键词： YOLO Tensors Accuracy Prototypes Wheels Cameras Hardware Maintenance Aircraft Aerospace industry

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Unobtrusive and Non-Invasive Human Activity Recognition using Kinect Sensor 2

Unobtrusive and Non-Invasive Human Activity Recognition usin...

引用

Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN 2020

作者： Nehra, Shalini Raheja, Jagdish Lal Control Automation Group Cyber Physical System Area CSIR-Central Electronics Engineering Research Institute Pilani India

ISBN: (纸本)9781728149998

The main objective of this paper is to present a depth imaging human activity recognition system that is basically used to monitor and detect normal activities of the person in the indoor environment. The Proposed system runs in real-time and is capable of detecting moving falls, sitting fall accurately and robustly without taking into account any false positive activities. Human activity recognition with high accuracy is a huge challenge in the research world. Fall detection is an important technology in health care and elderly person activity monitoring. The proposed method is feasibility and workability are illustrated throughout the experimental result that shows the perfect human tracking and activity detection. system works well with low lighting conditions;lighting does not affect the accuracy of detecting activities. Moreover, the proposed method is able to avoid false positive as: lying down, retrieve something from the floor. © 2020 IEEE.

关键词： Feature extraction

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Adaptive Multi-Core Real- Time Scheduling Based on Reinforcement Learning

Adaptive Multi-Core Real- Time Scheduling Based on Reinforce...

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International Conference on control and automation (ICCA)

作者： Yonghui Liang Hui Li Fei Shen Qimin Xu Shuna Hua Shanying Zhu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Re-search Center of Intelligent Control and Management Shanghai China Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China North Information Control Research Academy Group Company Ltd. Nanjing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

With the transformation towards industrial intel-ligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure exe-cution of sensing, computing and actuating tasks under time constraints. However, existing scheduling methods result in either low CPU utilization or many missed task deadlines in dynamic systems. In this paper, we propose a two-layer scheduling architecture to address this issue by fully exploring the complex dependency between real-time tasks. To be specific, the local layer determines task execution priorities considering both dependency between tasks and deadline constraints by utilizing a reinforcement learning approach. Moreover, to better utilize the parallel capabilities of multi-core processors and reduce temporal collisions, this paper minimizes the requested core count for the task set based on a greedy strategy. The global layer designs a scheduling algorithm based on the pre-empt method and provides schedulability analysis of multiple task sets. Experimental results validate the correctness of the proposed scheduling approach, and efficiency is demonstrated through comparisons with baseline method.

关键词： Job shop scheduling Multicore processing Scheduling algorithms Networked control systems Reinforcement learning Real-time systems Sensors

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High-Precision Admittance control of Mechanical Arm Based on Force Sensor Compensation

High-Precision Admittance Control of Mechanical Arm Based on...

引用

Chinese control and Decision Conference, CCDC

作者： Yaohui Wu Jiangbo Zhao Junzheng Wang Xin Zhang 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 Technical Center Xinxing Cathay International Group Co. Ltd. Beijing China

ISBN: (纸本)9781665478977

Admittance control is one of the important methods of compliance control. It is performed by inputting force signals and outputting position signals. Position control can achieve high accuracy, but the force signals have large errors, which is an important factor affecting its accuracy. When the force sensor collects force data, there are non-negligible initial deviations due to gravity, installation, and other factors, resulting in poor admittance control accuracy. In order to solve this problem, this paper takes the six-degree-of-freedom manipulator admittance control as the research object. According to the mapping relationship between the end attitude and the sensor errors, we propose a method of obtaining the initial offset value of the sensor through data interpolation. This method traverses the initial values of the sensor in each working posture when the sensor has no external force input, and then performs secondary interpolation to obtain the offset values of the sensor in any posture, corrects the output values of the force/torque sensor, and then improve the accuracy of admittance control. The experimental results show that this method can quickly and effectively improve the calculation accuracy of the sensor’s initial deviation values and the admittance control accuracy.

关键词： Interpolation Attitude control Force Dynamics Position control Robot sensing systems Real-time systems

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An Improved Safe Braking Model of Virtually Coupled Trains for Closer Tracking

An Improved Safe Braking Model of Virtually Coupled Trains f...

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IEEE International Conference on Networking, Sensing and control

作者： Wenxiao Yan Jiayu Wang Liqun Fan Qiusheng Liu Qingdong Jia Yihan Wang Hongjie Liu School of Automation and Intelligence Beijing Jiaotong University Beijing China Shenzhen Metro Group Co. Ltd. Shenzhen China Shenzhen Municipal Design and Research Institute Co. Ltd. Shenzhen China Traffic control Technology Co. Ltd. Beijing China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

With the rapid growth of transportation passenger flow in recent years, the research direction of Virtual Coupling (V C) in railways has become hot. V C increases capacity by tracking shorter distances. The traditional train emergency braking (EB) model can no longer meet the high operating efficiency requirements of VC. VC urgently needs a more efficient safety EB model. Therefore, to improve efficiency, a measurement of the EB model's rationality is defined considering safety and efficiency. Based on the defined model measurement, an EB model optimization method and a new EB model are proposed. The new model is closer to the actual braking process of the train and ensures safety from the distance level. That is, the braking trajectory of the train calculated by the new model is closer to the actual braking trajectory of the train, and the two braking trajectories satisfy the specific safety constraints. Finally, the safety and efficiency of the new model were verified through simulation experiments. The new model can avoid train collisions during the entire EB process. Experimental results show that compared with the traditional old EB model of VC based on space-time interval [1], the new model's minimum safe distance (MSD) between two VC train units can be reduced by 39%.

关键词： Couplings Analytical models Optimization methods Transportation Process control Safety Trajectory Sensors Brakes

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Research on Geomembrane Leakage Detection Method Based on Quadruped Robot

Research on Geomembrane Leakage Detection Method Based on Qu...

引用

Chinese automation Congress (CAC)

作者： Pengcheng Zhang Ningning Hu Xiao Wang Qingbiao Xi Haohao Zhao Xingchen Wu Linfeng Qin Dongli Yuan Investigation & Testing Research Institute Shanghai Investigation Design & Research Institute Co. Ltd. Shanghai China System Department 2 Xi'an ASN Technology Group Co. Ltd. Xi'an China School of Electronic and Control Engineering Chang'an University Xi'an China School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Aiming at the problem of leakage detection of seepage control geomembranes in landfills, a fully autonomous dipole method detection system based on a quadruped robot equipped with a dipole sensor is designed. The feasibility and superiority of using a quadruped robot are analyzed on the basis of the detection principle of the dipole method. Due to the problems existing in the process of upgrading the artificial static detection to autonomous dynamic detection, a dynamic detection method based on a quadruped robot is designed while the structure construction of the dipole method on the quadruped robot is completed. The experimental results show that the efficiency of geomembrane leakage detection can be improved with detection system method employed in this paper.

关键词： Legged locomotion Costs automation Landfills Dogs Robot sensing systems Software Quadrupedal robots Intelligent control

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An OpenPLC-based Active Real-time Anomaly Detection Framework for Industrial control systems

An OpenPLC-based Active Real-time Anomaly Detection Framewor...

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Chinese automation Congress (CAC)

作者： Chengxu Zheng Xiaopeng Wang Xiaoyu Luo Chongrong Fang Jianping He The Dept. of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China NSFOCUS Technologies Group Co. Ltd Beijing China

In recent years, the design of anomaly detectors has attracted a tremendous surge of interest due to security issues in industrial control systems (ICS). Restricted by hardware resources, most anomaly detectors can only be deployed at the remote monitoring ends, far away from the control sites, which brings potential threats to anomaly detection. In this paper, we propose an active real-time anomaly detection framework deployed in the controller of OpenPLC, which is a standardized open-source PLC and has high scalability. Specifically, we add adaptive active noises to control signals, and then identify a linear dynamic system model of the plant offline and implement it in the controller. Finally, we design two filters to process the estimated residuals based on the obtained model and use χ 2 detector for anomaly detection. Extensive experiments are conducted on an industrial control virtual platform to show the effectiveness of the proposed detection framework.

关键词： Adaptation models Industrial control Detectors Real-time systems Software Security Task analysis

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Review on the Two-layer Coordinated Architecture for Optimal Regulation and control of Energy Interconnection system in ew-type Towns 12

Review on the Two-layer Coordinated Architecture for Optimal...

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12th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2020

作者： Wang, Qi Li, Ning Gu, Xin Zhang, Nianchu Chen, Yonghua He, Guoxin Nanjing Normal University School of Electrical and Automation Engineering Nanjing China Simulation and Operation Control Nari Group Corporation Laboratory of Integrated Energy System Nanjing China

ISBN: (纸本)9781728157481

Energy interconnection system integrating 'Internet+' has become a new developing form of energy industry with the increase of Chinese urbanization level. It features the characteristics of multiple energy entities interconnection and independent decision. The decision-making structure, requirements of massive data processing, real-time communication and privacy security prevent the further application of centralized optimization method based on independent decision-making entities. Additionally, the difference of optimization among the energy entities cannot be ignored in the distributed optimization application. Integrating the concepts of 'cloud supervision' and 'weak centralization', this paper proposes a centralized distributed collaborative regulation and control architecture, and studies the decision-making method under this architecture to accelerate the local and global optimization. Based on this, this paper analyzes and summarizes the key technologies involved, including edge-cloud collaborative deployment mechanism, engineering data processing and service technology for energy interconnection system in new-type towns. The purpose is to provide a way to realize the optimal dispatch of energy interconnection system in new-type towns, and provide some suggestions for the development of energy interconnection system in new-type towns. © 2020 IEEE.

关键词： Global optimization

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An Improved Ensemble Deep Learning Model for Water Leakage Detection

An Improved Ensemble Deep Learning Model for Water Leakage D...

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第40届中国控制会议

作者： Shuwei Zhang Miaoshun Bai Jingcheng Wang Haotian Xu Shunyu Wu Dept of Automation Shanghai JiaoTong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Municipal Engineering Design Institute(Group)Co. Ltd

The leakage location for water supply system is a key point for the efficient operation and maintenance of urban water supply ***,the limited source of leakage dataset,high cost of leakage simulation experiments and the limited prediction accuracy of traditional models increase the difficulty of the leakage location for urban water supply *** paper proposes a new method based on ensemble learning method to address these *** software is employed in this paper for the generation of experimental *** leakage is located and predicted based on the hydraulic model of the water supply system through the design of the improved multi-model weighted voting mechanism for ensemble deep learning *** experiments show that the proposed method has higher precision and lower discretization compared to traditional models.

关键词： Water supply system Neural-network models Leakage detection Ensemble learning

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