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检索条件"机构=School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems"

共 2865 条记录，以下是2061-2070 订阅

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Bat Algorithm Optimizer for Drilling Trajectory Designing under Wellbore Stability Constraints

Bat Algorithm Optimizer for Drilling Trajectory Designing un...

引用

第37届中国控制会议

作者： Jiafeng Xu Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

In the process of deep geological resources exploration, there are often some complex stratigraphic situations. A threedimension drilling trajectory is designed by using the geological environment data. The trajectory should be sure that the target position is reachable. And it can avoid the area prone to be in an accident. In order to solve this problem, this paper discusses a three-dimensional wellbore trajectory design optimization model suitable for shale gas horizontal mining. Considering the wellbore stability and dogleg severity as constraints, the minimum drilling length is taken as the objective function. Depending on the Mohr-Coulomb criterion, the range of azimuth angle and inclination angle of safety trajectory can be determined. It can be seen as a constraint on the wellbore derrick segment. As for the optimization algorithm, bat algorithm（BA） optimizer combined with a penalty function method is applied to this optimization model. Finally, the case study shows that the BA performs well in the wellbore optimization design. It obtains the trade-off result between the safe and efficient drilling demands. And, it provides a basic model idea for the real-time trajectory optimization while drilling.

关键词： Drilling Trajectory Designing Wellbore Stability Bat Algorithm

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UKF based Fault Detection and State Estimation for Nonlinear systems with Correlated Noise 36

UKF based Fault Detection and State Estimation for Nonlinear...

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第36届中国控制会议

作者： Hongxue Chen Liping Yan Yuanqing Xia Mengyin Fu Bo Xiao Guangzheng Hu Huifang Li Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781538629185

State estimation and fault diagnosis are essential topics for dynamic *** Kalman fllter（UKF） has been widely applied in nonlinear *** classical UKF algorithm is built on the premise that process noise and measurement noise is *** practical problems,this assumption is not always *** addition,due to the limitation of communication and sensor fault,etc.,data missing or unreliable measurements will happen ***,it is very important to study the state estimation of nonlinear systems with unreliable measurements and correlated *** this paper,an UKF based state estimation algorithm with unreliable observations under correlated noise is presented.A numerical example is given to show the feasibility and effectiveness of the presented algorithm.

关键词： fault detection state estimation correlated noise nonlinear system

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A Detection System of Tool Parameter Using Machine Vision

A Detection System of Tool Parameter Using Machine Vision

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第37届中国控制会议

作者： Hantao Wang Hong Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

This paper suggests a novel technique for the tool parameter measurement based on machine vision. Tool images are captured by using a machine vision system and the outer contour image of the cutter is obtained by using the machine vision technology. The HALCON image processing library is used as the development platform to build the tool parameters test system. Several algorithms including image segmentation, edge extraction and fitting ellipse determination is used for image *** tool parameters such as external diameter and contour angle of tool edge can be obtained after rebuilding the contour of tool *** proposed scheme is shown to be reliable and effective for the automated tool parameter measurement.

关键词： Machine vision image processing tool parameter

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Multi-Convolution Neural Networks-Based Deep Learning Model for Emotion Understanding

Multi-Convolution Neural Networks-Based Deep Learning Model ...

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第37届中国控制会议

作者： Luefeng Chen Min Wu Wanjuan Su Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Tokyo Institute of Technology

Multi-convolution neural networks-based deep learning model in combination with multimodal data for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using multi-convolution neural networks, where multilayer convolutions are connected in series and multiple networks are executed in parallel. Moreover,when optimizing the weights of deep neural network by traditional method, it is easy to fall into poor local optimal. To address this problem, a hybrid genetic algorithm with stochastic gradient descent is developed, which has the capacity of inherent implicit parallelism and better global optimization of genetic algorithm so that it can adaptively find the better weights of the *** in order to speed up the convergence of the proposal, the weights optimized by stochastic gradient descent will be taken as a chromosome of genetic algorithms initial population, and it also can be used as a priori knowledge. To verify the effectiveness of the proposal, experiments on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-the-art methods. Meanwhile, the preliminary application experiments are also carried out and the results indicate that the proposal can be extended to human-robot interaction.

关键词： Deep learning emotion understanding convolution neural network facial expression body gesture

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Formation control for multiple agents with local measurements: continuous-time and sampled-data-based cases

Formation control for multiple agents with local measurement...

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IEEE Annual Conference on decision and control

作者： Chen Wang Shuai Li Weiguo Xia Jinan Sun Guangming Xie National Engineering Research Center for Software Engineering Peking University Beijing China State Key Laboratory of Turbulence and Complex Systems Peking University Beijing China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We study the formation control problem for a group of mobile agents in a plane, in which each agent is modeled as a kinematic point and can only use the local measurements in its local frame. The agents are required to maintain a geometric pattern while keeping a desired distance to a static/moving target. The prescribed formation is a general one which can be any geometric pattern, and the neighboring relationship of the N-agent system only has the requirement of containing a directed spanning tree. To solve the formation control problem, a distributed controller is proposed based on the idea of decoupled design. One merit of the controller is that it only uses each agent's local measurements in its local frame, so that a practical issue that the lack of a global coordinate frame or a common reference direction for real multi-robot systems is successfully solved. Considering another practical issue of real robotic applications that sampled data is desirable instead of continuous-time signals, the sampleddata based controller is developed. Theoretical analysis of the convergence to the desired formation is provided for the multiagent system under both the continuous-time controller with a static/moving target and the sampled-data based one with a static target. Numerical simulations are given to show the effectiveness and performance of the controllers.

关键词： Robot kinematics Coordinate measuring machines Mobile agents Multi-robot systems Sun Collision avoidance

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Correlation-based dynamics and systemic risk measures in the cryptocurrency market 16

Correlation-based dynamics and systemic risk measures in the...

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16th IEEE International Conference on Intelligence and Security Informatics, ISI 2018

作者： Liang, Jiaqi Li, Linjing Zeng, Daniel Zhao, Yunwei State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China

ISBN: (纸本)9781538678480

Cryptocurrency is a rapid developing financial technology innovation which has attracted a large number of people around the world. The high-speed evolution, radical price fluctuations of cryptocurrency, and the inconsistent attitudes of monetary authorities in different countries have triggered panic and chain reactions towards the application and adoption of cryptocurrency and have caused public security related events. So far, a lot of researches and analyses have focused on just one or only a few number of cryptocurrencies, a comprehensive analysis of the whole cryptocurrency market and its systemic risk is still lacking. In this paper, we analyze the dynamics and systemic risk of the cryptocurrency market based on the public available price history. We first validated that the correlation matrix and asset tree are good tools to analyze the risk and stability of the cryptocurrency market. Furthermore, consistent with public perception, our quantitative analysis reveals that the cryptocurrency market is relatively fragile and unstable. Our work is the first to investigate the systemic risk of the whole cryptocurrency market and may shed some light on cryptocurrency related investment decision, regulation, and legislation. © 2018 IEEE.

关键词： Blockchain

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Comparison of control Methods Based on Imitation Learning for Autonomous Driving

Comparison of Control Methods Based on Imitation Learning fo...

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International Conference on intelligent control and Information Processing (ICICIP)

作者： Yinfeng Gao Yuqi Liu Qichao Zhang Yu Wang Dongbin Zhao Dawei Ding Zhonghua Pang Yueming Zhang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China The state Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China China Automotive Technology & Research Center Co. Ltd Tianjin China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology China

ISBN: (数字)9781728100159

ISBN: (纸本)9781728100166

Recently, some learning-based methods such as reinforcement learning and imitation learning have been used to address the control problem for autonomous driving. Note that reinforcement learning has strong reliance on the simulation environment and requires a handcraft design of the reward function. Considering different factors in autonomous driving, a general evaluation method is still being explored. The purpose of imitation learning is to learn the control policy through human demonstrations. It is meaningful to compare the control performances of current main imitation learning methods based on the provided dataset. In this paper, we compare three typical imitation learning algorithms: Behavior cloning, Dataset Aggregation (DAgger) and Information maximizing Generative Adversarial Imitation Learning (InfoGAIL) in the The Open Racing Car Simulator (TORCS) and Car Learning to Act (CARLA) simulators, respectively. The performance of algorithms is evaluated on lane-keeping task in racing and urban environment. The experiment results show DAgger performs best in simple lane keeping problem, and InfoGAIL has the unique advantage of distinguishing different driving styles from expert demonstrations.

关键词： Gallium nitride Trajectory Data models Entropy Task analysis Linear programming Autonomous vehicles

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Attention-based multi-hop reasoning for knowledge graph 16

Attention-based multi-hop reasoning for knowledge graph

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16th IEEE International Conference on Intelligence and Security Informatics, ISI 2018

作者： Wang, Zikang Li, Linjing Zeng, Daniel Dajun Chen, Yue State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China

ISBN: (纸本)9781538678480

Knowledge graph plays an important role in detection, prediction, early warning, and other security related applications. A fundamental task in applying knowledge graph is the so-called multi-hop reasoning, which focuses on inferring new relations between entities. In this paper, we introduce attention mechanism to the classic compositional method. After finding reasoning paths between entities, we aggregate these paths' embeddings into one according to their attentions, and infer the relation of entities based on the combined embedding. Two experiments on NELL-995 dataset, fact prediction and link prediction, validated that our method outperforms all baselines. © 2018 IEEE.

关键词： Forecasting

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Calculation Method of Load Distribution for Two-crane Cooperative Lift

Calculation Method of Load Distribution for Two-crane Cooper...

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第37届中国控制会议

作者： Xiaoling Shen Jianqi An Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Cooperative lifting by two cranes is widely used in the current construction site. Since the influence of changeable load in the cooperative lifting process, it is essential to take the load distribution into consideration while planning the lifting path to ensure the safety of the whole lifting process. However, most researches did not consider the reasonable actual load distribution or just used a certain load in the lift process. This paper analyzes the relationship between crane operations and the pose of the lifted object. Then based on this relationship, this paper gives the method calculating the distribution of actual load over each crane that the planning approach is based. This paper also gives calculation methods and constraints for the skew angle of each lifting rope. The results of simulation show the effectiveness of this calculation method.

关键词： Cooperative Lifting Actual Load Calculation

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An intelligent Selection Strategy for Burden Distribution Based on Classification of Blast Furnace Condition

An intelligent Selection Strategy for Burden Distribution Ba...

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第37届中国控制会议

作者： Kexin Zhang Min Wu Jianqi An School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace(BF).However, due to the low transparency of this process, operators adjust the burden distribution according to their own experiences,which makes it difficult to keep optimal production indexes for a BF. In this paper, an intelligent selection strategy of burden distribution is devised according to the energy-consuming index, where carbon-monoxide utilization rate(CMUR) is taken as the energy-consuming index. First, state variables are chosen based on the calculated Pearson correlation coefficient among each state variable. Then, the chosen state variables are divided into five clusters by k-means clustering algorithm. Finally, the values of CMUR in each condition cluster with different burden distribution are counted. According to the statistics, the burden distribution with the highest CMUR is judged to be the optimal one. Simulation results based on industrial data show that the proposed strategy selects the optimal burden distribution and provides a reasonable guide for the operators.

关键词： Burden distribution blast furnace k-means carbon-monoxide utilization rate

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