bluuebunny/crossref_metadata_2025 huggingface dataset:
An Approach to Edge Extraction Based on 3D Point Cloud for Robotic Chamfering
Authors: Wang Yongzhi , Du Zhijiang , Gao Yongzhuo , Li Mingyang , Dong Wei
Published: July 2019

Inconsistency of workpieces always results in low level automation of subsequent finishing process. As decreasing number of skilled workers, the demands of flexible manufacturing with robots is growing. In this paper, a kind of workpiece with complex free-form surface will be chamfered by industrial robots. Due to the intolerant differences among workpieces, traditional teach-playback method for robot is not appropriate for this application. The edge spline of each workpiece needs to be detected so that trajectories are generated to chamfer. Thus, an approach to edge extraction based on a 3D point cloud obtained by the 3D industrial camera is introduced to solve this problem. A time optimizing method is proposed to accelerate the extraction process. Finally, we decrease computing time from 55 minutes to 300 seconds, and the precision is 0.4180 mm.
New Research on Transfer Learning Model of Named Entity Recognition
Authors: Guan Guoliang , Zhu Min
Published: July 2019

This paper integrates the current Google’s most powerful NLP transfer learning model BERT with the traditional state-of-the-art BiLSTM-CRF model to solve the problem of named entity recognition. A bi-directional LSTM model can consider an effectively infinite amount of context on both sides of a word and eliminates the problem of limited context that applies to any feed-forward models. Google’s model applied a feedforward neural network, causing its performance to weaken. We seek to solve these issues by proposing a more powerful neural network model named BT-BiLSTM. The new neural network model has obtained F1 scores on three Chinese datasets exceeds the previous BiLSTM-CRF model, especially on the value of recall. It shows the great value of the combination of large scale none-labelled data pre-trained language model with named entity recognition, which inspire new ideas on other future work.
Detection of Non-Standard English Expressions by Language Sense
Authors: Chao Li , Jingxiang Zhang
Published: July 2019

This paper proposes an algorithm for perception English essay, in order to improve the ability of Chinese students’ writing which expressing more standard. Because students are influenced by their mother tongue in second language acquisition, English expression is not accurate enough. From the lexical and syntactic aspects, this paper uses the language sense relevance analysis algorithm (N-LanSen) based on the N-model to deeply perceive the students’ inappropriate expression in the essay. Different extraction methods are used to extract different features, and the corresponding feedback can be given to the places where the expression is not standard. The experimental results show that the algorithm can detect the place where English expression is not standard with high accuracy.
Study on Reactive Power Imbalance and Its solution of Parallel Coupled Transmission Lines
Authors: Li Dengfeng , Liu Yuming , Xiang Bin , Li Xiaoju , Si Meng , Yang Mincai
Published: July 2019

In view of the imbalance and even the abnormal phenomenon of reactive circulation of parallel high voltage transmission lines with similar measured parameters in actual operation, combined with field investigation and test, theoretical analysis and simulation demonstration, it is clear that this phenomenon is caused by the use of unconventional phase sequence and unreasonable transposition of the two-circuit lines when erecting the same tower. Based on the PSCAD simulation, the corresponding improvement measures are put forward from two aspects of optimizing the arrangement of phases and transposition. The results show that in order to solve the power imbalance problem of parallel coupled transmission lines, it is recommended to optimize the phase sequence of conductors in consideration of economy and operability.
Review of Research on Task-Oriented Spoken Language Understanding
Authors: Hou Lixian , Li Yanling , Li Chengcheng , Lin Min
Published: July 2019

Spoken language understanding(SLU) is an important function module of the dialogue system. Slot filling and intent detection are two key sub-tasks of task-oriented spoken language understanding. In recent years, the methods of joint recognition have become the mainstream methods of spoken language understanding to solve slot filling and intent detection. Since deep neural network has advantages such as strong generalization and autonomous learning characteristics compared with traditional methods. So far, slot filling and intent detection have been developed from traditional methods to deep neural network methods, and the performance has also been significantly improved. This paper introduces the methods of two tasks from the independent model to the joint model. It focuses on the joint modeling methods based on deep neural network, analyzes current problems and future development trend of two sub-tasks.
De-Noising Algorithm for Flight Data Recording System Based on Modified Ensemble Empirical Mode Decomposition
Authors: Dai Shaowu , Chen Qiangqiang , Dai Hongde
Published: July 2019

The Flight Data Recording System (FDRS) records a lot of parameters of the aircraft during flight, which can be used for the test-flying, training mission of aircraft and so on. Effected by the working environment, information interference and its non-stability, the outliers and noise often exists in the FDRS data. These noises and outliers have a great impact on the use of FDRS. The aim of this paper is to remove outliers and de-noising of navigation data in FDRS. The causes of outliers and noise in FDRS data are analyzed firstly, with a reference suggestion proposed. Then the Letts criterion is used to remove outliers and the Modified Ensemble Empirical Mode Decomposition (MEEMD) is applied to achieve denoising for FDRS. Results demonstrate that outliers are removed and the navigation data are de-noised effectively.
Positioning and Tilt Correction of Milk Production Date Based on Mathematical Morphology
Authors: Lei Fei , Sun Kang , Wang Xueli
Published: July 2019

Milk is one of the most common drinks in people’s lives. Its quality is related to people’s health and safety. Therefore, food regulatory authorities and milk manufacturers are increasingly strict with milk. The production date on the packaging is an important part of milk testing. One. Aiming at the problems of long time and high cost of manual detection, this paper proposes a method based on mathematical morphology for milk production date location and tilt correction based on computer vision related technology. The method firstly preprocesses the collected milk image, then uses the mathematical morphology method to obtain the candidate region of the milk production date, then analyzes the candidate region, extracts the accurate milk production date region, and finally uses the least squares principle. The straight line is fitted to calculate the tilt angle of the milk production date, and the milk image is tilt corrected using the rotation formula. In order to verify the comparison with the Hough transform method, the experiment proves that the proposed method can accurately predict the milk production date and tilt correction.
A Target Detection Method Based on Statistical Mean Value Difference Model
Authors: Lei Fei , Long Kai , Wang Xueli
Published: July 2019

In the field of oil pipeline monitoring applications, the guarantee of high accuracy target detection is required. Aiming at the problem of moving target detection under static camera, a method of mean background model based on probability and statistics is proposed. The background model is quickly constructed. The background threshold is adaptively used to eliminate the influence of illumination changes. The target is detected quickly and accurately. Finally, the proposed target is proposed. The background update method updates the background model in real time. The simulation results show that the better detection results can be obtained under the influence of light changes. The background model has strong stability and adaptability, and can be applied to the real-time monitoring system of the field oil pipeline.
Multi-agent Consensus Problem Based on Observer and Considered Lur’e Nonlinearity in Directed Topology
Authors: Zhou Shaolei , Zhao Xueyuan , Yan Shi , Wang Shuailei
Published: July 2019

This paper studies the multi-agent systems consensus problem considering Lur’e-type nonlinearity under directed network. Compared with the conclusions of the existing undirected communication topology, the conclusions obtained have greatly reduced the communication topology requirements and are more general. This paper designs a control protocol based on the observer, which solves the problem that the system state information is unknown. By decomposition of a specific form of the Laplacin matrix, consensus problem is converted into stability problem for low-dimensional systems. In this paper, the method of solving the control protocol is given and proved by the piecewise Lyapunov function. The simulation results show that the designed control protocol can solve the consistency problem.
Exploring Multiple Embedded Features on Event Extraction
Authors: Yi Shi-Xiang , Li Chun-Yan
Published: July 2019

In recent years, the neural network method can automatically learn effectively features. Unlike traditional discrete features, neural network features are mostly continuous features and can be automatically combined to build higher-level features. The efficiency of the features has been proven in numerous tasks in natural language processing and has led to breakthroughs. In this paper, we propose a event extraction system based on combination of multiple embedded features. Our work is mainly based on the three aspects: (1) traditional pipeline systems have serious error propagation problems; (2) there are several different event descriptions in the text; (3) representation learning can provide rich semantic and syntactic representation. As a result, we achieve competitive performance, specifically, F1-measure of 60.25 in event extraction. Meanwhile, evaluation results point out some shortcomings that need to be addressed in future work.
Common Sensors in Industrial Robots: A Review
Authors: Li Peng , Liu Xiangpeng
Published: July 2019

The application of industrial robots has greatly promoted the development of industry in the past decades. Now with the proposal and prevalence of Industry 4.0, industrial robots are required to be more independent and intelligent to accomplish more complex and flexible tasks. The advancement of industrial robots relies on the development and progress of multiple technologies, among which sensors are the indispensable part. They can acquire abundant information to help industrial robots implement their functions. This paper reviews the recent literatures and gives a summary and introduction of the commonly used sensors in industrial robots. Additionally, the applications of these sensors in diverse functions of industrial robots are also presented. Finally, the developing direction and challenges of industrial robots in the future are discussed in the last part of this article.
An Improved Negatively Correlated Search Inspired by Particle Swarm Optimization
Authors: Qun Niu , Bing Liu , Kecheng Jiang , Han Wang
Published: July 2019

Negatively correlated search (NCS) is a latest intelligence algorithm which maintains multiple individual search processes in parallel and models the behavior of individual search processes using probability distributions. In this paper, an improved NCS inspired by particle swarm optimization (PSO) is proposed, namely PSO-NCS. This algorithm introduces the global best solution (gbest) and personal best solution (pbest) from PSO to calculate the Bhattacharyya Distance (BD) of individuals in the population, which greatly reduces the computational time. Experimental results on six 100 dimensional functions and 10 CEC2005 benchmark functions show that the proposed PSO-NCS has outstanding capability in solving the optimization problems and outperforms the conventional NCS and other methods on most of the test functions. The computational time has been greatly shortened, which saves about 65% in average compared to NCS.
Research on a Fast Continuous Vialog Algorithm
Authors: Jinning Zhang , Yishu Zhou , Huayang He , Lishuo Ren
Published: July 2019

Surface evenness affects vehicle safety, service life, and passenger comfort. The road surface with poor flatness will produce resistance to the vehicle driving, making the vehicle vibrate and bump, hindering the safety of the vehicle driving, and will also cause local water accumulation, speed up the road damage and so on. In order to make the vehicle safe, passengers feel comfortable, road life growth, road flatness detection is particularly important.In order to make the vehicle safe to travel, passengers feel comfortable, the road service life growth, and the detection of road surface evenness is particularly important. In order to overcome the shortcomings of the existing algorithms for pavement evenness, this paper has put forward a new fast algorithm that can be applied to the continuous vialog, and according to the elevation value obtains the evenness standard deviation σ. The results show that the algorithm is high reliability, which provides a reference for the upgrade of instruments and equipment, and makes up for the shortcomings that the continuous vialog cannot be tested quickly.
Research and Optimization of Real-time Simultaneous Localization and Mapping of Indoor Robot Based on Binocular Vision
Authors: Zhang Qiwei , Zhou Guanglu , Wang Pengpeng , Wu Fengguang
Published: July 2019

For the problem of inaccuracy and cumulative error of visual odometer, The research and optimization of real-time Simultaneous Localization and Mapping of indoor robot based on binocular vision are studied. Based on ORB-SLAM2, key-frame map is created. First, the ORB feature is extracted from each frame of the input image and matched by fast approximation nearest neighbour(FLANN). Then, perform the preliminary pose estimation using EPnP, and optimize it with bundle adjustment and key-frame maps. When the tracking fails, apply key-frame maps and bag of words model to relocate. Finally, for the input binocular image, the SGBM is used to solve the parallax and then the depth, which will be converted to radar format data to create a map. In the research and optimization of real-time Simultaneous Localization and Mapping of indoor robot based on binocular vision, propose a method of assisted positioning with key frame map, and a method of feature matching optimization and relocation, which combines various pose optimization to achieve the accuracy of the robot indoors positioning and map construction.
Analysis of Competitive Situation in Basic Research of Global Intelligent Robots
Authors: Rong Li , Ru Liu , Zichao Luo , Jing Liu
Published: July 2019

Practically grasp the global development trend of the basic research on intelligent robots and provide support for the scientific development of intelligent robots in China. Relying on bibliometrics, this paper has proposed a four-dimensional competitive situation analysis system for basic research based on activeness and talent distribution, etc., which can effectively analyze the global situation of basic research on intelligent robots, able to reveal and describe the competition status quo and situation of the basic scientific research in specific fields. There is a big gap between China and the United States in basic research on intelligent robots, mainly including such aspects as follows: uneven distribution of high-level basic research talents; insufficient international cooperation in high-level scientific research; lower research activeness; layout of key research and development.
CNN-LSTM Combined Network for IoT Enabled Fall Detection Applications
Authors: Xu Jun , He Zunwen , Zhang Yan
Published: July 2019

An accidental fall could do a great damage to the health of elderly. Failure to provide timely assistance after a fall may cause injury or even death. In this paper, a fall detection algorithm based on Convolutional Neural Network (CNN)-Long Short Term Memory (LSTM) combined network is proposed, which makes full use of the powerful feature extraction ability of CNN and the excellent time series processing ability of LSTM. Data required by the algorithm is only the resultant acceleration from a low cost three-axis acceleration sensor. The experimental results show that compared with the algorithms based on Support Vector Machine (SVM) and CNN, the proposed algorithm has higher detection accuracy with a small data volume, which is very suitable for Internet of Things (IoT) enabled fall detection applications.
Parametric Design of Grasshopper Based on Moulding Characteristics of Longitudinal Profile of Shoe Last
Authors: Tian Yujing , Miao Yuxin , Yu Ying , Zhang Ziran
Published: July 2019

In order to achieve low-cost, high-efficiency customized footwear design and service to meet the individual needs of customers, quickly producing various types of shoe last based on different needs has become the key to customization. According to the moulding characteristics of the longitudinal profile of the shoe last, the key characteristic parameters and morphogenesis logic are found. Combined with the parameterized nonlinear thinking feature, the parameter logic is constructed. Rhino’s parametric design plug-in Grasshopper is used to develop the shoe last design process. The automatic moulding process of the sectional view, combined with the parametric design of the shoe last and the cross-section of the shoe last, can form a quick custom shoe last method. A professional and rapid design method is formed to enhance the design and production efficiency of customized shoe lasts.
A Novel Line Feature Description and Matching Method for Visual-Aided Inertial Navigation System
Authors: Guang Xingxing , Gao Yanbin , Liu Pan , Li Guangchun
Published: July 2019

With the rapid development of machine vision technology, more and more attention has been paid to the visual-aided inertial navigation system. It is important that to extract and track the line features at the dynamic situation in the visual-aided inertial navigation system which is based on visual line feature information to compensate attitude errors. A novel line feature description is proposed that use the SURF points to mark the LSD lines. Then, through coarse matching and fine matching, the function of continuously tracking the one line features in different images was realized. These line feature description and tracking method are applied in the visual-aided inertial navigation system, and its effectiveness is verified by the vehicle experiment.
Semantic Segmentation of Remote Sensing Images via Stepwise-Refined Large-Kernel Deconvolutional Networks
Authors: Xinwei Zhao , Haichang Li , Rui Wang , Changwen Zheng , Song Shi
Published: July 2019

Deep CNN based semantic segmentation has been developed for several years and many models are proposed. However, most of them are designed for natural scene images such as PASCAL VOC, and cannot perform very well on remote sensing images, in which objects are much smaller and more densely distributed than those in natural scene images. In this paper, we demonstrate the importance of high-resolution feature maps and the problem of large dilated convolutional kernels in semantic segmentation of remote sensing images. Furthermore, we propose a Stepwise-Refined Large-Kernel Deconvolutional Network with a focus on small and densely-distributed objects such as houses and buildings, or long and narrow ones such as roads and rivers. Experiments on a public available ISPRS Vaihingen Challenge Dataset and our self-compiled Fujian Dataset show that our model outperforms the state-of-the-art models in semantic segmentation of remote sensing images.
Design of a Synchronous Control System for Mobile Lift Based on Wireless Network
Authors: Zhuang Lu , Chen Haijin
Published: July 2019

The lift used in automobile maintenance industry is usually installed in a place permanently. It occupies the place, and also has poor adaptability to vehicles with different size. Furthermore, there exists physical connection between lifting columns, which affects maintenance operation. To solve these problems, a mobile hydraulic lift control system based on wireless network has been designed. It uses the STM32F103 microcontroller and nRF905 wireless communication module to form a control network for several mobile lifts. The height of each lift is measured with laser displacement sensors, and synchronously controlled through the wireless control network. The control system was verified by lifting the Jinlong bus with wirelessly connected four lifts. The lifting process is stable, which demonstrates a bright prospect for practical usages.
A Human-Robot Interaction for a Mecanum Wheeled Mobile Robot with Real-Time 3D Two-Hand Gesture Recognition
Authors: Luo Xueling , Amighetti Andrea , Zhang Dan
Published: July 2019

Human interaction with mobile robot becomes a popular research area and its applications are widely used in industrial, commercial and military fields. A two-hand gesture recognition method with depth camera is presented for real-time controlling the mecanum wheeled mobile robot. Seven different gestures could be recognized from one hand for mobile robot navigation and three gestures could be recognized from the other hand for controlling the gripper installed on the robot. Under the proposed control scheme, the mobile robot system can be navigated and can be operated at the same time for achieving missions by two different groups of hand gestures. The accuracy of the gesture recognition is about 94%. During mobile robot control experiment, the system works timely, accurately and stably for certain tasks such as directional movement, grasping and cleaning obstacles.
Mechanics Modeling and Kinetic Analysis of Sub Marine Tracked Vehicle-Cable Salvage during Steady-state Steering
Authors: Hao Zhang , Jianjun Su , Xiaoli Hu , Yubing Duan , Xin Shi , Jinxia Yao , Chao Gu
Published: July 2019

Based on the demand for deep-sea submarine cable salvage in Northeast Asia, a mathematical model of Sub Marine Tracked Vehicle-Cable Salvage (SMT-CS) was designed in this study. Considering the slip characteristics of the submarine track, the mechanical model of the SMT-CS during steady-state steering was simplified to obtain the kinetic equation of the vehicle body during steady-state steering. According to the steering geometrical relationship, the arbitrary shear rate and shear displacement of the ground plane during the steering process were solved. Combined with the empirical shear model of bottom sediments, the longitudinal driving force, lateral resistance and resistance moment of the larboard and starboard were derived during steady-state steering. The functional relationship between the lateral shift of instantaneous center of the conventional steering rate and the turning radius and angular velocity of the vehicle body as well as that between the slipping rate and the turning radius and angular velocity of the vehicle body was derived according to the geometrical relationship of steering motion. These are of great reference value to the design, performance prediction and maritime application of SMT-CS in the future.
Event-triggered Group Consensus for First-order Multi-agent Systems Based on Directed Topology
Authors: Zhou Shaolei , Wang Shuailei , Yan Shi , Zhao Xueyuan
Published: July 2019

Event-triggered group consensus problem is addressed in this paper. Based on the assumption named the in-degree balance, a directed first-order multi-agent system is constructed, which consists of two subgroups. To analyze the problem, the Laplacian matrix of the initial system is decomposed to be two matrices with less row and column dimension. Then the initial state vector can be substituted by a new one, each element in which is the error of two adjacent elements of the initial state vector. Then a new reduced-order system is constructed and the consensus problem is converted to a stability problem. With the designed Lyapunov function, the validity of the proposed algorithm is proved. The lower-bound of the inter-event time interval is also presented. Simulation results are presented to demonstrate the effectiveness of the protocol.
ABB Robotic Arm Offline Programming System
Authors: Xu Zhe , Liu Yuanjiang
Published: July 2019

The offline programming technology of industrial robots is more and more widely used because it can effectively improve work efficiency. A DXF drawing file is a file generated by CAD that can serve as a bridge for data exchange with other software. Through experiments, this paper combines CAD-generated DXF drawing files with ABB robotic arm to realize data extraction of CAD drawings, and automatic generation and storage of robotic arm running programs, which are imported into the robot arm, so that the robot arm can be made according to CAD. The trajectory on the drawing performs the welding function. The simulation of path planning was carried out under the Robot studio software developed by ABB Robotics to meet the experimental requirements. The realization of this off-line programming system achieves the following two purposes. One is to assist non-control professional teaching, to help understand the simulation and actual production and processing of industrial robot arm; the second is to improve the efficiency of industrial robot arm programming and realize full automation programming.
The Design and Application of FEU: Automation Monitoring Unit for 5G base stations
Authors: Li Hong , Liu Huazhao , Yan Baiyi
Published: July 2019

In order to realize the co-construction, sharing and intensive management of millions of stations across the network, supporting 5G go into operation efficiently, China Tower Group has developed a new generation of intensive and distributed operation maintenance monitoring platform over the inherited mobile base stations from the three major telecom operators. Based on the development and the application of this platform, FEU (an intelligent Power and Environment Monitoring Unit) is proposed, which uses the dynamic shared library method to embed the edge gateway to realize the edge computing capability of China Tower’s intelligent operation and maintenance platform. It effectively solves the normalized monitoring of heterogeneous FSU and massive sites, constructs the intensive operation maintenance capability for China Tower and lays a solid foundation for the tower-based IoT [1, 2] expansion business.
A Novel Network Traffic Prediction Method Based on RMPM
Authors: Wu Jianjun , Gong Weijun , Shang Zhen
Published: July 2019

The network traffic prediction plays the key role in congestion control and bandwidth allocation. A variety of traditional learning models such as artificial neural networks (ANN) have been applied in prediction. To avoid the drawbacks of traditional models for prediction, a novel robust minimax probability machine (RMPM)-based traffic prediction method is proposed in this paper. The prediction performance is tested on two different types of traffic data, Ethernet data flow and MPEG4 video flow, at the timescale 1. The experiments demonstrate that the proposed method attains satisfactory performance in prediction accuracy. Therefore, the proposed method can be used for congestion control or bandwidth allocation, to meet the user QOS requirements.
Design of By-Pass Excitation Cable Force Sensor
Authors: Yishu Zhou , Ping An , Jinjin Cao , Jinning Zhang , Chang Liu
Published: July 2019

With the continuous progress of bridge technology and the requirements for bridge aesthetics, cable technology is increasingly widely used in long-span bridges. Due to the long-term environment of alternating stress, corrosion and wind-induced vibration, it is easy to cause local fatigue and damage of the cables, which endangers the safety of the entire bridge structure. The sleeve cable force sensor based on magnetic flux method is widely used in practical engineering among many measurement methods. Existing sleeve cable force sensors need to be installed at the beginning of construction, so it is difficult to reinstall them in the follow-up, and its long-term performance is also difficult to evaluate and measure online. To solve this problem, this paper introduces the design of a kind of magnetic flux cable force sensor with by-pass excitation, and presents its measuring principle and design structure. The designed by-pass excitation cable force sensor is expected to solve the problem of the existing sleeve sensor.
Design of Management and Control System of Aero-engine Nozzle Processing Line
Authors: Chang Kai , Zheng DeChao , Yin Jian , Tan Guangchao
Published: July 2019

This paper introduces a kind of management and control system of machining production line for aero-engine nozzle. The main logistics is based on the logic control of PLC, which can dispatch a robot to realize the automatic transfer of the parts between workstations, automatic feeding and unloading of processing and testing equipment. Workstations are equipped with RFID to detect the identification of each nozzle. The system can reconstruct the process route according to the nozzle type, associate processing and test data of the nozzle with their identification number to establish the processing file. It realizes data exchanges between management and control systems by OPC interface, achieves centralized monitoring and control of the equipment of the whole line and improves the informatization level of workshop.
Tire-Pavement System Modelling and Triaxial Contact Stress Analysis
Authors: Minrui Guo
Published: July 2019

In the pavement design, the tire load is usually assumed to be a circular or rectangular evenly distributed load, which is actually not like this. In order to provide data reference for the development of tire-pavement contact stress intelligent test instrument, it is necessary to model the tire-pavement system, and construct tire-pavement 3D finite element model using large finite element software. Firstly, establish three-dimensional model of tire and road surface, and impose certain loads and constraints. Secondly, the triaxial contact stress of the tire-pavement under static conditions is analyzed. Then the triaxial stress under traction conditions is analyzed, and the triaxial stress under different conditions of use of the tire is compared and analyzed. The results show that as the load of the tire gradually increases, the maximum vertical contact stress and the maximum longitudinal stress gradually decrease, but the maximum lateral pressure gradually increases. When the inflation pressure of the tire is gradually increased, the contact stresses in the three directions are correspondingly increased. However, the maximum vertical contact stress and maximum longitudinal stress increase more obviously than the maximum transverse contact stress. In addition, the transverse contact stress could be ignored under traction conditions.
PD Control at the Hopf Bifurcation Point of a Neuron System with Inertia and Delay
Authors: Shi Shuo , Wang Huaifei , Xiao Min
Published: July 2019

In this paper, a two-neuron system with inertia and delay is proposed firstly. a PD controller is then applied to the system for the purpose of improving its dynamical performance. Through the mathematical transformation, we extend the system to a four-dimensional one with only time delays. With the help of the associated characteristic equation of the mathematical model, suffcient conditions for ensuring the system stability are proposed. Furthermore, with the time delay as the bifurcation parameter, relevant requirements for the generation of Hopf bifurcation are derived. Then a series of numerical simulatiosns are carried out to justify the theoretical analysis and it is found that the application of PD control scheme helps to advance the bifurcation point dramatically through a slight adjustment of the controller parameters.
On the Equivalent Position Workspace for a Coal Gangue Picking Robot
Authors: Liu P , Ma H W , Zhang X H , Qiao X Z
Published: July 2019

Coal gangue separation is of key important for green mining. Robotic separation of coal and gangue based on the machine vision system, which is called a coal gangue picking robot with a gangue grab driven by four cables, is developed in this study. Here, this paper focuses on the equivalent position workspace, within which a coal gangue picking robot possesses the identical stability, to find out any more information about the structural stability for a coal gangue picking robot. First, the kinematic and kinetostatic models of the coal gangue picking robot are presented for analyzing the effects of it on the structural stability for the coal gangue picking robot. And moreover, a non-iterative polynomial-based optimization algorithm with the proper optimal objective function is presented based on the convex optimization theory, in which the cable with the minimum cable tension at any pose is determined. Then, three position performance indices are proposed to show the important effects on the structural stability for the coal gangue picking robot in a specified region of the workspace. Besides, a new workspace, the Equivalent Position Workspace (EPW), is introduced. Finally, the theoretical relationship between the two performance indices and the stability is corrected based on simulation results. The research has important guiding significance and practical value for coal gangue robotic separation.
Fault Tolerant Consensus with Multiagent Systems for Distributed Coordinated Control Algorithm in the Energy Internet Network
Authors: Hsieh Chung-Hung , Ming Chen Yee
Published: July 2019

The future power system can be considered as an aggregation of controllable distributed systems devices that coordinate with each other through the Internet of Things (IoT), energy internet (EI) new paradigms arise. In EI environments, agreement among multiple computers is essential for power generation, transmission, distribution, and consumption etc. applications. Coordinated control and security protection play important roles in the application of a distributed computing environment. A consensus approach can provide fault tolerance and prevent system errors and attacks, thereby providing the system with strong security in distributed computing environment. In this paper, a distributed Kalman filter with consensus coordinated control algorithm for multiagent systems (MAS) was proposed to investigate the energy internet with links failure by cyber attack. The proposed algorithm is evaluated in the energy internet through a MAS model using MATLAB software.
Research on the Guidance Law for UAV Rendezvous Based on Virtual Leader
Authors: Wen J X , Zhao G R , Li X B , Han X
Published: July 2019

The rendezvous of UAVs as a first step in the formation of a UAV is crucial. In this paper, a maneuvering system based on virtual leader is proposed. Firstly, the relative kinematics model of the virtual leader and UAV is established, and then a proportional guidance law with falling angle constraint is designed to make the UAV. Finally, the desired attitude angle can be achieved, and the speed of the UAV can be controlled, so that the UAV can track the virtual leader at a set speed and maintain a relative distance, thereby achieving the purpose of formation flying. The simulation results show that this method can effectively guide the formation of UAVs and has certain engineering application value.
Two-Stage Backward Elimination Method for Neural Networks Model Reduction
Authors: Tang Xiaoquan , Zhang Long
Published: July 2019

The single-hidden-layer neural networks (NN) has been widely used for complex system identification. However, the hidden neurons are often determined by trial-and-error method and the amount of neurons is usually large. This commonly leads to over-fitting problem and the training process is time consuming. In this paper, we propose a two-stage backward elimination (TSBE) method to obtain a parsimonious network with fewer hidden neurons but remains a good performance and saves training time. In the first stage, neural networks with a predetermined number of hidden neurons is trained based on stochastic gradient decent (SGD) algorithm with part of training data and Least absolute shrinkage and selection operator (Lasso) is applied for dropping redundant neurons leading to a simplified neural model. In the second stage, the remaining training data is used to update the parameters of the simplified neural model. A simulation example is used to validate and show that the novel approach gives a more compressed model and higher level of accuracy comparing with the recently proposed pruning-based method.
Complex Dynamic Behaviors of A Congestion Control System under A Fractional-order PD Control
Authors: Lu Qiu , Wang Huaifei , Xiao Min , Si Lingzhi
Published: July 2019

This paper proposed an original fractional-order proportional-derivative (PD) feedback controller which is designed to control the Hopf bifurcation caused by the congestion control system. The proposed

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controller has the different order with the original congestion system. The proposed fractional-order PD controller has the different order with the controlled system and the communication delay is selected as the bifurcation parameter. Then the conditions of the stability and Hopf bifurcation are obtained by analyzing its characteristic equation and the stability domain can be extended under the adjustment of appropriate control gain parameters and the order. Therefore, the congestion system becomes controllable and the desirable behaviors can be realized. Finally, numerical simulations are carried out to testify the validity of the theoretical analysis in the designed fractional-order PD controller.
Design and Simulation of Variable Structure PI Controller
Authors: Shaojun Liu , Yuyu Wang
Published: July 2019

Aiming at the poor performance of IP control system in tracking continuously varying input signals, a variable structure PI controller was proposed, which can eliminate overshoot of step response and track continuously varying input signals without error. The controller performs as an IP controller for step input signals and a PI controller for continuously changing input signals. Firstly, the control performance defects of traditional IP controller were analyzed, and then the structure of variable structure PI controller was built. Finally, the simulation results show that the VSPI and IP control systems have the same control effect when the step signal is input. Compared with PI control system, the VSPI and IP control systems not only have no overshoot but also have better response stability. When the input is a continuous sinusoidal signal, VSPI and PI can track the input signal almost without error, and the control effect is obviously better than IP control. The anti-jamming performance of the system is inversely proportional to the bandwidth value, but has nothing to do with the control mode.
Sliding Mode Attitude Control of Quadrotor UAV Based on Proportional Integral Observer
Authors: Wang Zitong , Wan Youhong
Published: July 2019

This paper designs a sliding mode self-pose attitude controller for a quadrotor unmanned aerial vehicle (UAV) system based on proportional integral observer, which also considers the problem of external disturbances. In this paper, firstly, considering the influence of external disturbance, a proportional integral observer is developed to contains the ratio of the estimated error and the integral loopobtain, and obtain both the estimation of the system state and unknown input. Then, the stability of the state estimation error of the proportional integral observer is proved. Thirdly, based on the results of the proportional integral observer, a sliding mode attitude controller is designed. This method is simple and easy to implement, which can improve the system robustness and eliminate the chattering phenomenon existing in the traditional sliding mode control. Finally, the simulation results show that the UAV system achieves better control effect and dynamic performance.
The Architecture of a Driverless Robot Car Based on EyeBot System
Authors: Sun Shuangquan , Zheng Jingwen , Qiao Zihan , Liu Shanqi , Lin Zihan , Bräunl Thomas
Published: July 2019

This paper presents the system architecture of a driverless robot car, designed to participate in the Carolo-Cup, a competition regarding automated model vehicles. We describe an implementation that completed the different tasks in this competition on our EyeBot platform in detail. EyeBot has one RGB camera as well as three infrared distance sensors, and it’s powered by Raspberry Pi 3B. We developed the lane detection algorithm using the OpenCV library and completed the traffic sign recognition task based on SVM which can be used offline. Experimental and simulation results recorded in real-time are also reported. The test result showed that our programs can run at high speed to achieve stable motion control in real time and complete all the tasks in the competition. The highlight of our work is that the whole system can run on a platform with limited computing resources.
Kinematic and Static Analysis and Experimental Study for Dual-arm Continuum Robot
Authors: Gao Guohua , Zheng Yuhang , Wang Hao
Published: July 2019

The continuum robot, which is different from the traditional rigid robot, consists of a flexible structure, and becomes a research hotspot in the field of robots, because of its good flexibility and adaptability in the complex environment. According to the advantages of the continuum robot, it could be applied in medical, exploration and agricultural operations. This paper proposed a cable-driven dual-arm continuum robot with three-degree-of-freedom. The kinematics of posture parameters and driving parameters, as well as the statics, was established. And the dual-arm coordinated reachable work space was described according to the principle of constant curvature deformation, on the basis of which, the theoretical motion model of the continuum robot was simulated using MATLAB, and experiments of the posture of the dual-arm continuum robot was conducted on the prototype to verify the accuracy of the theoretical kinematics and statics model.
The macroeconomic impacts of future river flooding in Europe
Authors: Koks E E , Thissen M , Alfieri L , De Moel H , Feyen L , Jongman B , Aerts J C J H
Published: July 2019

The economic impacts of disasters can reach far beyond the affected regions through interconnected transboundary trade flows. As quantification of these indirect impacts is complex, most disaster risk models focus on the direct impacts on assets and people in the impacted region. This study explicitly includes the indirect effects via regional economic interdependencies to model economic disaster losses on a continental scale, exemplified by river flooding in Europe. The results demonstrate that economic implications go beyond the direct damages typically considered. Moreover, we find that indirect losses can be offset by up to 60% by economic actors through finding alternative suppliers and markets within their existing trade relations. Towards the future, increases in economic flood losses (up to 350%) can be expected for all global warming scenarios. Indirect losses rise by 65% more compared to direct asset damages due to the increasing size of future flood events, making it more difficult to offset losses through alternative suppliers and markets. On a sectoral level, future increases in losses are highest for commercial services (∼980%) and public utilities (∼580%). As the latter are predominately affected through cascading effects, this highlights how interdependencies between economic actors could amplify future disaster losses.
Impacts of climate change on tomato, a notorious pest and its natural enemy: small scale agriculture at higher risk
Authors: Litskas Vassilis D , Migeon Alain , Navajas Maria , Tixier Marie-Stéphane , Stavrinides Menelaos C
Published: July 2019

Climate change (CC) clearly impacts food production, but risks on the climatic suitability of agricultural areas for vegetable crops, their pests and associated natural enemies are largely unexplored. Tomato, one of the most important vegetables in the world, is grown mostly outdoors, and may be severely impacted by CC. Farmers cultivating tomatoes need to adapt to an increase in the potential for outbreaks of pests favoured by CC and disruption of biological control, yet, no attempt has been made to simultaneously evaluate CC effects on a crop-pest-natural enemy system for tomato or any other crop. Here, we modelled the suitability of areas equipped with irrigation facilities (AEI) in 2050 for tomato, the two-spotted spider mite, Tetranychus urticae, a mite pest of tomato among more than 200 crops, and its key predator Phytoseiulus persimilis. We evaluated the suitability of AEI for tomato production under a 1.6 °C warming by 2050, within the targets of the Paris agreement. Projections show that climatic conditions become unsuitable for tomato production on 30%–100% of AEI for seven out of the 29 top tomato producing countries of the world. Model predictions suggest that two-spotted spider mite potential for outbreaks would increase substantially in nine countries in Europe, Africa and Asia, while biological control failures would occur globally. Model results have a significant relationship with growth rates for the three species measured in outdoor experiments, and farmer/expert perceptions on two-spotted spider mite outbreak severity captured via interviews. The expansion of AEI in other agricultural areas in the sub-Saharan Africa may offset losses of suitable land. However, several nations in the Middle East and South Asia with prevalent small scale agriculture would experience devastating impacts because of the unsuitability of conditions for tomato production and the potential increase in two-spotted spider mite outbreaks.
Negative carbon isotope excursions: an interpretive framework
Authors: Vervoort P , Adloff M , Greene S E , Kirtland Turner S
Published: July 2019

Numerous negative carbon isotope excursions (nCIEs) in the geologic record occurring over 104–105 years are interpreted as episodes of massive carbon release. nCIEs help to illuminate the connection between past carbon cycling and climate variability. Theoretically, the size of a nCIE can be used to determine the mass of carbon released, provided that the carbon source is known or other environmental changes such as temperature or ocean pH can be constrained. A simple isotopic mass balance equation often serves as a first order estimate for the mass of carbon input, but this approach ignores the effects of negative carbon cycle-climate feedbacks. Here we show, using 432 earth system model simulations, that the mass of carbon release and associated environmental impacts for a nCIE of a given size and carbon source depend on the onset duration of that nCIE: the longer the nCIE onset duration, the greater the required carbon input in order to counterbalance the input of 13C-enriched carbon through carbonate compensation and weathering feedbacks. On timescales >103 years, these feedbacks remove carbon from the atmosphere so that the relative rise in atmospheric CO2 decreases with the nCIE onset duration. Consequently, the impacts on global temperature, surface ocean pH and saturation state are reduced if the nCIE has a long onset duration. The framework provided here demonstrates how constraints on the total nCIE duration and relative shape—together determining the onset duration—affect the interpretation of sedimentary nCIEs. Finally, we evaluate selected well-studied nCIEs, including the Eocene Thermal Maximum 2 (∼54 Ma), the Paleocene–Eocene Thermal Maximum (∼56 Ma), and the Aptian Oceanic Anoxic Event (∼120 Ma), in the context of our model-based framework and show how modeled environmental changes can be used to narrow down the most likely carbon emissions scenarios.