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IEEE International Conference on Mechatronics and Automation

作者： Enzeng Dong Bo Han Xiao Yu Shengzhi Du Complex System Control Theory and Application Key Laboratory Tianjin University of Technology (TJUT) Tianjin China

In order to improve the detection effect of the single Gaussian background model (SGM), an improved SGM algorithm is proposed to detect moving targets in this paper, which has made three improvements on the base of SGM. Firstly, the algorithm adopts adaptive background learning rate instead of using a fixed learning rate. Secondly, we use a new update strategy of Gaussian background model, which makes the Gaussian background model has good convergence and stability. Finally, the moving targets are detected according to the principle of Gaussian distribution and the image morphology filtering. Experimental results show that the background model of improved SGM can adapt well to background changes, and the target detection integrity is higher than that of the traditional SGM.

关键词： Adaptation models Computational modeling Morphology Filtering Feature extraction Object detection Gaussian distribution

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Research on Intelligent Monitoring system of Greenhouse Intensity and CO2 Concentration Based on STM32

Research on Intelligent Monitoring System of Greenhouse Inte...

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IEEE International Conference on Mechatronics and Automation

作者： Shuanzeng Li School of Electrical and Electronic Engineering Tianjin Key Laboratory of complex system control theory and Application Tianjin China

Because the stability and accuracy of the traditional greenhouse monitoring system are not high enough, the light intensity and the grape canopy of the intelligent monitoring system are established for this phenomenon. It is based on the CO2 concentration of STM32 single chip to monitor the intensity of light and CO2 concentration and show it at the same time. Serial communication is used to send test results to MCGS touch screen to achieve real-time monitoring and warning of light intensity and CO2 concentration in greenhouse. The result of long term test shows the precision of the light intensity detection of the system is 9401ux, CO2 concentration measurement accuracy 40ppm. Compared with the traditional automatic monitoring system, the system runs stably and costs less, and the accuracy meets the requirements of grape greenhouse. In conclusion, the system proposed in this paper is suitable for agriculture.

关键词： Pipelines Green products Monitoring Voltage control Real-time systems Oscillators Air pollution

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EEG controlled Automated Writing Robotic Arm Based on Steady State Visually Evoked Potential

EEG Controlled Automated Writing Robotic Arm Based on Steady...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement systems and applications

作者： Xuequan Zhu Meng Mu Abdelkader Nasreddine Belkacem Duk Shin Rui Xu Kun Wang Zhongpeng Wang Changming Wang Chao Chen Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin China Zhonghuan Information College Tianjin University of Technology Tianjin China College of Information Technology UAE University Al Ain UAE Tokyo Polytechnic University Atsugi Japan Academy of medical Engineering and Translational medicine Tianjin University Tianjin China Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China

ISBN: (数字)9781538683446

ISBN: (纸本)9781538683453

Brain-Computer Interface(BCI) refers to devices that allow people to communicate or control the outside devices only through brain waves without relying on their own output pathways, such as the human nervous system and muscle tissue. The problem of insufficient information transfer and interaction between organism and electromechanical device in electromechanical integration system is pointed out. This paper uses BP(Brain Products) equipment to collect Steady State Visual Evoked Potential (SSVEP) signals. The collected SSVEP signals were preprocessed, feature extracted and feature classified. Then it is connected with the robot arm to build a portable brain-computer interface control system. Six subjects participated in the online experiment of the system. Experimental results show that the system can write some simple Chinese characters with high accuracy, and the system is feasible and effective. Then the signal is taken by Open Brain-computer Interface (OpenBCI) to complete the connection with the robotic arm. We will realize the control of the robotic arm in the later experiment. Our research aim is to find an relatively effective control method by comparing BP and OpenBCI based control on the robotic arm.

关键词： Erbium

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Simultaneous Location and Map Construction Based on RBPF-SLAM Algorithm

Simultaneous Location and Map Construction Based on RBPF-SLA...

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第30届中国控制与决策会议

作者： Hong He YunHui Jia Lei Sun School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application

Solving the problem of simultaneous location and map construction（SLAM） is the core of robot autonomous navigation. At present, most algorithms usually only consider the odometer information of mobile robot, therefor, there exists some problems of increasing computation amount caused by a large number of sampling particles and the complexity. So, this paper developed a scheme of map construction and positioning based on RBPF-SLAM algorithm. The hardware and software platform is set up on the ROS, and it merge the odometer information of the robot into the distance information collected by the laser sensor, which effectively reduces the number of required particles and the uncertainty of the robot’s pose estimates in filter prediction phase. Through the experimental, get the conclusion: simultaneous positioning based on RBPF-SLAM algorithm and map construction system can create high-precision online raster map in real time, and it is more consistent with the actual map.

关键词： ROS RBPF-SLAM Algorithm Simultaneous Location Laser Sensor Pose Estimates

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Research on Online Testing system of Flow Characteristics for Vehicle Electronic Fuel Injector

Research on Online Testing System of Flow Characteristics fo...

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IEEE International Conference on Mechatronics and Automation

作者： Yanhao Li Bin Liu Jianwen Li Yan Zhao Wei Lei Tianjin Key Laboratory for Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin China Military Transportation University Tianjin China

Complied with relevant standards, a novel on-line testing system for flow characteristics of electronic fuel injector was proposed in this paper. The designed structure of the system was described in details, as well as the composition and principle of the control unit. The testing process on the dynamic flow and the static flow of the port fuel injectors driven by voltage was implemented. According to the experimental results, the error of the on-line system is less than 4%, which can meet the requirements on flow characteristics test of fuel injectors. At the same time, the on-line system has practical application values.

关键词： Fuels Testing Valves Vehicle dynamics Standards Solenoids Flowmeters

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Co-design of Model-Reference Scheduling and control

Co-design of Model-Reference Scheduling and Control

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第37届中国控制会议

作者： Shunli Zhao Yuehui Ji Tianjin Key Laboratory for Control Theory & Applications in Complicated System Tianjin University of Technology School of Electrical and Electronic Engineering Tianjin University of Technology

There have been growing concerns in networked control system with communication *** the paper,a model-reference scheduling scheme is proposed for optimizing the distribution of the network *** states are determined to gain the access to the network by computing the difference between the real system and the ideal *** stability analysis and the joint design of the controller and scheduling are given by formulating the problem as a linear equality equation that can be solved *** proposed strategy is evaluated through a simple simulation.

关键词： Networked control system model-reference co-design scheduling

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Correction to: A method of VR‑EEG scene cognitive rehabilitation training

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Health information science and systems 2021年第1期9卷 7页

作者： Wenjun Tan Yang Xu Pan Liu Chunyan Liu Yujin Li Yanrui Du Chao Chen Yuping Wang Yanchun Zhang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang 110189 China. Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou 510006 China. Department of Neurology Xuanwu Hospital Capital Medical University Beijing 100053 China. Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin 300384 China. Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne VIC 8001 Australia.

[This corrects the article DOI: 10.1007/s13755-020-00132-6.].

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Switching Power Supply Design Suitable for Motor control 29

Switching Power Supply Design Suitable for Motor Control

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第29届中国控制与决策会议

作者： Zhi-Chao Zhao Li guo-hong Tianjin University of Technology Tianjin Complex System Control Theory and Application Key Laboratory

ISBN: (纸本)9781509046584

Motor control systems require multi-channel stable output low voltage DC power *** to the needs of motor control system,a switching power supply can meet the requirements of motor control is *** topology of switching power supply and the uses of PWM control chips are *** positive and negative bias generation circuit of IGBT is *** circuit components' choices and design method of a high frequency transformer of the flyback switching power supply are ***,the basic performances of switching power supply were tested;the results show that it can meet the requirements of motor control systems.

关键词： switching power supply motor drive pulse width control chip high frequency transformer

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Summary of medical robot technology development 15

Summary of medical robot technology development

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Zhang, Xu Ma, Xu Zhou, Jinpeng Zhou, Qi Tianjin Key Laboratory of High Speed Cutting and Precision Maching School of Mechanical Engineering Tian jin University of Technology and Education Tianjin300130 China Tianjin Key Laboratory for Control Theory and Applications in Complicated System School of Electrical and Electronics Engineering Tian jin University of Technology Tianjin300384 China Tian jin University of Technology Tianjin300384 China School of Mechanical Engineering Hebei University of Technology Tianjin300130 China

ISBN: (纸本)9781538660720

In the past few decades, medical robots have developed rapidly. In this paper, medical robots are divided into the following categories based on the application of medical robots: neurosurgery robots, orthopedic robots, endoscopic surgery robots, instrutive robots, rehabilitation-assisted robots and capsule robots. The research and application status of typical surgical robots at home and abroad are briefly introduced, and medical 3D image modeling, virtual surgery simulation, open-source surgical systems, and remote surgery in complex environments involved in medical robots are studied. key technologies were discussed, and the future direction of medical robots was pointed out. © 2018 IEEE.

关键词： Medical imaging

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An Improved Convolution Neural Network for Object Detection Using YOLOv2

An Improved Convolution Neural Network for Object Detection ...

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IEEE International Conference on Mechatronics and Automation

作者： Enzeng Dong Yanfang Zhu Yuehui Ji Shengzhi Du Complex System Control Theory and Application Key Laboratory School of Electrical and Electronic Engineering Tianjin University of Technology (TJUT) Tianjin China

You Only Look Once (YOLO) is an object detection system with real-time effects. It is difficult to accurately detect small targets in complex scenes, so an improved network structure of YOLOv2 is proposed in this paper. The proposed network is improved in the following aspects: firstly, a 1×1 convolutional layer is added to improve the detection accuracy;secondly, the output sizes of several layers are changed from 13×13 to 26×26 to extract more features from multi-pixels image;thirdly, the loss function is also optimized to adapt to the size of objects in the image. Finally, the model is trained and tested based on VOC2007 dataset, and the experiment results show that the improved model has higher accuracy on detecting small objects.

关键词： Object detection YOLOv2 VOC2007 Detection accuracy

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