检索结果-内蒙古大学图书馆

IEEE Canada Electric Power Conference, EPEC

作者： Md Rezwan Parvez Wenkai Hu Tongwen Chen University of Alberta Edmonton Alberta Canada School of Automation and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

ISBN: (数字)9781728164892

ISBN: (纸本)9781728164908

Alarm floods are considered to be the major obstacles that prevent the smooth process operations of large-scale industrial facilities. During an alarm flood situation, industrial operators often get confused by too many alarms and thus have difficulties in observing and handling critical alarms. In recent years, sequence alignment based similarity analysis has emerged as an effective way to handle alarm floods. Alarm floods caused by the same fault are very likely to consist of the same group of alarms in a certain sequential order. Conducting realtime sequence alignment of industrial alarm floods can help operators to quickly recall the root cause and make prompt corrective actions. This paper proposes the online similarity analysis of alarm floods based on the Smith-Waterman and Needleman-Wunsch algorithms, and compares their differences and application conditions. Case studies are provided to illustrate the proposed online similarity analysis methods and the differences of the two sequence alignment algorithms.

关键词： Heuristic algorithms Indexes Prediction algorithms Power systems Pattern matching Frequency measurement Conferences

来源：评论

学校读者我要写书评

暂无评论

Analytic Hierarchy Process（AHP） in Portfolio Selection Based on Information Granularity

Analytic Hierarchy Process（AHP） in Portfolio Selection Bas...

引用

第32届中国控制与决策会议

作者： Kaixin Zhao Yaping Dai Ye Ji Jiayi Sun School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Analytic Hierarchy Process（AHP） is a multi criteria decision-making method,which can describe and transform the qualitative problems quantitatively,and then get the quantitative analysis results in accordance with the causal relationship between decision *** this paper,a granular Analytic Hierarchy Process,which introduces the granularity mechanism,is proposed to solve the portfolio selection problem under the mean-risk *** the proposed method,the scale value of scheme layer is no longer limited to nine positive integers from 1 to 9,which gives granularity attributes to the comparison of advantages and disadvantages in a specific criterion layer between different *** proposed method reflects small differences between different alternative schemes through granularity attribute,so it can provide rich decision information for decision *** numeric examples from the real-world financial market（China Shanghai Stock Exchange） are provided to illustrate an essence of the proposed method.

关键词： Analytic Hierarchy Process（AHP） Portfolio Selection Information Granularity Decision-making

来源：评论

学校读者我要写书评

暂无评论

DBFCM: a Density-Based Fuzzy C-Means with Self-Regulated Fuzzy Clustering Parameters

DBFCM: a Density-Based Fuzzy C-Means with Self-Regulated Fuz...

引用

第三十九届中国控制会议

作者： Jiayi Sun Yaping Dai Kaixin Zhao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

As an interdisciplinary of fuzzy theory and clustering, Fuzzy C-Means（FCM） is widely applied for identifying categories with unlabeled data. However, its application to data which is hard to visualize rises the difficulty for users to determine the input parameters, especially for the number of clusters. In this paper, a kind of fuzzy clustering algorithm with self-regulated parameters named Density-Based Fuzzy C-Means（DBFCM） is proposed by integrating the idea of Density-Based Spatial Clustering of Application with Noise（DBSCAN） into FCM. Its advantage is using the inherit density characteristic of input data to self-determine the parameters of fuzzy clustering. The experimental results demonstrate that the proposed DBFCM can not only self-determine the proper parameters, but also accelerate the convergence process compared to the original FCM.

关键词： Machine Learning Fuzzy Clustering Fuzzy C-Means Parameter Self-Regulation

来源：评论

学校读者我要写书评

暂无评论

Motion Planning of Six-DOF Arm Robot Based on Improved DDPG Algorithm

Motion Planning of Six-DOF Arm Robot Based on Improved DDPG ...

引用

第三十九届中国控制会议

作者： Zhuang Li Hongbin Ma Yazhe Ding Chen Wang Ying Jin School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

This paper presents an improved deep deterministic policy gradient algorithm based on a six-DOF(six multi-degree-offreedom) arm robot. First, we build a robot model based on the DH(Denavit-Hartenberg) parameters of the UR5 arm robot. Then,we improved the experience pool of the traditional DDPG(deep deterministic policy gradient) algorithm by adding a success experience pool and a collision experience pool. Next, the reward function is improved to increase the degree of successful reward and the penalty of collision. Finally, the training is divided into segments, the front three axes are trained first, and then the six axes. The simulation results in ROS(Robot Operating System) show that the improved DDPG algorithm can effectively solve the problem that the six-DOF arm robot moves too far in the configuration space. The trained model can reach the target area in five steps. Compared with the traditional DDPG algorithm, the improved DDPG algorithm has fewer training episodes,but achieves better results.

关键词： Motion Planning Improved DDPG Six-DOF Arm Robot ROS

来源：评论

学校读者我要写书评

暂无评论

Local Map Construction Based on 3D-LiDAR and Camera

Local Map Construction Based on 3D-LiDAR and Camera

引用

Chinese control Conference (CCC)

作者： Hui Qin Jing Li Junzheng Wang Qingbin Wu Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

The local map can update the local environment information in real time, which provides the environment information for the local dynamic planning of the robot. In this paper, a local cost map construction method based on 3D-LIDAR and camera is proposed. We use camera to detect lane lines in structured road and 3D-LIDAR to detect road boundaries in unstructured environment, and then use DS evidence reasoning to determine the current local road information. Dynamic obstacle information in the environment is obtained through 3D point cloud data segmentation, which is fused with the road information to get 3D point cloud information in the local range and generate local cost map according to it. Experiments show that the method in this paper can accurately extract the current road information whether in structured roads or unstructured roads. The fused local cost map can enable the robot to perform reasonable local planning and complete navigation on the current road.

关键词： Roads Three-dimensional displays Robots Planning Cameras Real-time systems Navigation

来源：评论

学校读者我要写书评

暂无评论

Design of Simultaneous State and Unknown Input Filtering Algorithm for a Class of Nonlinear Stochastic systems with Multiple Sensors

Design of Simultaneous State and Unknown Input Filtering Alg...

引用

IEEE International Conference on Cloud Computing and Intelligence systems (CCIS)

作者： Zhibin Hu Jun Hu Cai Chen Junhua Du Department of Applied Mathematics Harbin University of Science and Technology Harbin China School of Automation Harbin University of Science and Technology Harbin China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology Harbin China College of Science Qiqihar University Qiqihar China

ISBN: (纸本)9781665456579

In this paper, we investigate the simultaneous state and unknown input (SUI) filtering issue for a class of multi-sensor networked systems (MSNSs). The unknown input with no prior knowledge is introduced in the system state and output. The focus of this paper is to design the local filters with regard to the SUI, which can yield that the local upper bounds of the filtering error covariance for the SUI are derived at each instant. Moreover, the local filter gains of the SUI are designed such that the obtained upper bounds can be minimized. Finally, the proposed joint SUI algorithm is verified by using the simulation example.

关键词： Cloud computing Upper bound Filtering Stochastic systems Computational modeling Filtering algorithms Forward error correction

来源：评论

学校读者我要写书评

暂无评论

Robotic arm calibration and teaching method based on binocular vision

Robotic arm calibration and teaching method based on binocul...

引用

第三十九届中国控制会议

作者： Ming Chen Xin Hong Longsheng Wei Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems CRRC Zhuzhou Locomotive Co. Ltd.

Aiming at the errors caused by the production and assembly of the robotic arm and the problem of low absolute positioning accuracy, a method of robotic arm calibration and teaching based on binocular vision is proposed in this paper. First,the joints of the robot arm is controled to rotate separately, and the motion trajectory data of the end of the robot arm is recorded by the binocular vision. Then the circle center and circle plane normal vector of each joint axis motion is optimized using Adam algorithm. After identification and calculation, accurate kinematic parameters are obtained, and then kinematically model the manipulator once again. After the calibration is completed, the user can use the teaching rod to define the trajectory under the camera, and the defined trajectory is converted to the robot arm coordinate system for inverse kinematics solution. Finally, the robotic armis controled to reproduce the trajectory. Experimental results show that the proposed method can complete the precise calibration of the kinematic parameters of the robotic arm. After calibration, the average error of the end of the robotic arm is within 1 mm, and the absolute positioning accuracy is improved by more than 80%. The method proposed in this paper has low cost and simple operation, and it is easy to be popularized and applied in industrial and desktop robotic arm calibration and teaching.

关键词： Binocular vision Calibration Kinematic modeling Teaching Positioning accuracy

来源：评论

学校读者我要写书评

暂无评论

$H_{\infty }$ PID control for Discrete-Time Fuzzy systems With Infinite-Distributed Delays Under Round-Robin Communication Protocol

引用

IEEE Transactions on Fuzzy systems 2021年第6期30卷 1875-1888页

作者： Yezheng Wang Zidong Wang Lei Zou Hongli Dong College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Computer Science Brunel University London Uxbridge U.K. Institute of Complex Systems and Advanced Control and the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University Daqing China

This article is concerned with the $H_{\infty }$ proportional–integral–derivative (PID) control problem for class of discrete-time Takagi–Sugeno fuzzy systems subject to infinite-distributed time delays and round-robin (RR) protocol scheduling effects. The information exchange between the sensors and the controller is conducted through a shared communication network. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. To stabilize the target system with guaranteed $H_{\infty }$ performance index, a novel yet easy-to-implement fuzzy PID controller is developed whose integral term is calculated based on the past measurements defined in a limited time window with hope to improve computational efficiency and reduce accumulation error. Based on the Lyapunov stability theory and the convex optimization technique, sufficient conditions are derived to ensure the exponential stability as well as the $H_{\infty }$ disturbance attenuation/rejection capacity of the underlying system. Furthermore, by utilizing the cone complementarity linearization algorithm, the nonconvex controller design problem is transformed into an iterative optimization one that facilitates the controller implementation. Finally, simulation examples are given to show the effectiveness and correctness of the developed control method.

关键词： PD control Protocols PI control control systems Symmetric matrices Communication networks Optimization

来源：评论

学校读者我要写书评

暂无评论

Survey on 6D Pose Estimation of Rigid Object

Survey on 6D Pose Estimation of Rigid Object

引用

第三十九届中国控制会议

作者： Jiale Chen Lijun Zhang Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems CRRC Zhuzhou Locomotive Co. Ltd.

Estimating 6 D pose of rigid objects has gained increasing attention as it has become an curcial problem in rapidly growing technology related to robotics, augmented reality and autonomous driving. Therefore, the research on 6 D pose estimation technology is of great significance. In this paper, firstly, current position of the field is summarized regarding object pose estimation. We found that deep learning combined with traditional methods can produce better results. Then, pose ambiguity which is an open problem needed further study is raised. Finally, the main problems of the current research and possible development directions are identified.

关键词： Pose Estimation Feature Detection Pose Ambiguity

来源：评论

学校读者我要写书评

暂无评论

Noise Modeling and Data Augmentation Using Conditional Adversarial Autoencoder

Noise Modeling and Data Augmentation Using Conditional Adver...

引用

第三十九届中国控制会议

作者： Yunkai Jiang Yuan Zhu Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems CRRC Zhuzhou Locomotive Co. Ltd.

Noising image recognition is an important but challenging task. The images collected by the camera are often accompanied by a variety of noise, which will cause the loss of image information to make recognition difficult. With powerful feature extraction, neural network models can be used to process these complex noising images. However, when the noise model to be learned is complex and the number of learning samples is limited, this may lead to overfitting of the network model. In order to increase the diversity of noising images in limited learning samples and improve the generalization ability of the recognition model, we propose a noise modeling method based on CVAE-GAN. First, the encoder maps a real noising image to hidden layer vectors, which contains noise distribution, image category, and pose information. Then the decoder receives these hidden layer vectors to generate an synthetic image of the specified category and noise level. Finally, during the training process, we combine adversarial loss and smoothl1 loss to make the generated noising image more realistic. Experiments show that compared with other current generative models, our method can more effectively learn the distribution rules of complex noise in real images and generate synthetic images more similar to real noise. These synthetic images generated by our method can can alleviate the overfitting problem caused by insufficient data volume and enhance the generalization ability of image recognition models. By this way, we obtain the state-of-the-art recognition performance on the challenging noising image dataset.

关键词： Noising Image Data Augmentation Recognition Noise Modeling Weak Supervision

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：