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2017 IEEE International Conference on Unmanned systems (ICUS)

作者： Muyun Jiang Jiahui Shi Hongbin Ma You Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538631089;9781538631072

This paper presents an air-ground coordinated system made up of an Unmanned Aerial Vehicle(UAV) and an Unmanned Ground Vehicle(UGV).The movement of UGV is totally controlled by UAV and multiple sensors are adopted in the system to ensure the stability.A novel neutral network algorithm is introduced to identify the location and orientation of *** component is introduced and tested in detail and the coordinated system performs a satisfying result.

关键词： Air-ground system Neutral Network

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Advances in Vision-Based Lane Detection：Algorithms,Integration,Assessment,and Perspectives on ACP-Based Parallel Vision

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IEEE/CAA Journal of Automatica Sinica 2018年第3期5卷 645-661页

作者： Yang Xing Chen Lv Long Chen Huaji Wang Hong Wang Dongpu Cao Efstathios Velenis Fei-Yue Wang Advanced Vehicle Engineering Centre Cranfield University Bedford MK43 0AL U.K Vehicle Intelligence Pioneers Ltd Qingdao 266000 China School of Data and Computer Science Sun Yat-Sen University Guangzhou 510275 China Mechanical and Mechatronics Engineering with the University of Waterloo 200 University Avenue West Waterloo ON N2L 3G1 Canada State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China ieee

Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system,and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.

关键词： advanced driver assistance systems(ADASs) ACP theory benchmark lane detection parallel vision performance evaluation

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Optimization Oriented Performance Assessment for Combustion Process of Coke Oven

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IFAC-PapersOnLine 2017年第1期50卷 13778-13783页

作者： Lei, Qi Wu, Min Liu, Guoping School of Information Science and Engineering Central South University ChangshaHunan410083 China School of Automation China University of Geosciences WuhanHubei430074 China School of Engineering University of Southwales PontypriddCF37 1DL United Kingdom Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubei430074 China CTGT Center Harbin Institute of Technology HaerbinHeilongjiang150001 China

This paper presents an optimization oriented performance assessment method for combustion process of coke oven by integrating analytic hierarchical process (AHP) and intuitionistic fuzzy(IF) set. An AHP model is built up including safety, stability and economic considerations. To handle the complexity in the combustion process of coke oven, where the decision maker usually has some uncertainty in assigning preference values to the index considered, the IF set is used to obtain the IF preference. Entropy and cross entropy are applied to calculate the weights of the individual indices. The comprehensive evaluation method integreated the AHP and IF can effectively solve the performance assessment for the combustion process of the coke oven. Finally, the data obtained from the process model in different operating conditions are used to demonstrate the effectiveness. © 2017

关键词： Coke ovens Coke Combustion Decision making Fuzzy sets Hierarchical systems Analytic hierarchical process Combustion pro cess Comprehensive evaluation Different operating conditions Economic considerations Entropy methods Intuitionistic fuzzy Performance assessment

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Efficient Deployment of Patrols to Catch Arsonists

Efficient Deployment of Patrols to Catch Arsonists

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Chinese automation Congress (CAC)

作者： Jinpeng Han Fei-Yue Wang Yisheng Lv Fenghua Zhu Yilun Lin Xingyuan Dai Li Li School of Software Engineering Xian Jiaotong University Xian China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing Qingdao Academy of Intelligent Industries Qingdao Shandong The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China Department of Automation Tsinghua University Beijing China

Forest fires are serious disasters that endanger the safety and property of residents. To deal with the arson-caused forest fires, we use security game theory to generate optimal patrol strategy under limited patrolling resources. The existing security game algorithms focus on a single behavior model to prevent attacks, while our work is to incorporate the secondary damage caused by the attack behavior into the optimization object. For forest fires, the security game algorithm only expects to catch arsonists in the forest, which is unreasonable in our opinion. Our algorithm incorporates the spread of fires into patrolling path planning so that defenders avoid being swallowed by fire via capturing the spread of it.

关键词： Games Forestry Security Game theory Mathematical model automation control systems

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Stability analysis of switched nonlinear delay systems with sampled-data inputs

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International Journal of Robust and Nonlinear control 2019年第14期29卷

作者： Zhichuang Wang Jian Sun Guoliang Chen Jie Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

This study addresses the uniformly globally asymptotically stability (UGAS) problem of switched nonlinear delay systems (SNDSs) with sampled-data inputs (SDIs). By using multiple Lyapunov functionals (MLFs) method, mode-dependent average dwell times, and the total activating time length of MLFs, some stability criteria are explicitly obtained for SNDSs with SDIs. Meanwhile, the UGAS property for SNDSs with some or all unstable modes is investigated. For unstable modes and stable modes, we adopt different switching signals. Besides, we establish some sufficient stability conditions in the form of an upper bound on the sum of dwell times and sampling intervals. Simulation examples are adopted to illustrate and verify the effectiveness of our proposed methods.

关键词： multiple Lyapunov functionals sampled-data inputs stability switched nonlinear delay systems

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An Improved Result on H∞ State Estimation for Static Neural Networks with Time-Varying Delay

An Improved Result on H∞ State Estimation for Static Neural...

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第36届中国控制会议

作者： JIN Li HE Yong ZHANG Chuan-Ke WU Min School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper presents an improved result on H state estimation for static neural networks with a time-varying ***,a novel Lyapunov-Krasovskii functional(LKF) with several augmented terms is ***,a relaxed integral inequality is employed to make a tight estimation for single integral terms with time-varying delay in the derivative of the *** a result,a delay-dependent criterion in terms of linear matrix inequalities is ***,two numerical examples are given to demonstrate the benefits and effectiveness of the obtained criterion.

关键词： Static neural networks Time-varying delay H∞ state estimation Lyapunov-Krasovskii functional Relaxed integral inequality Linear matrix inequality

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H∞ state estimation for discrete time-delayed stochastic genetic regulatory networks with known sojourn probabilities 23

H∞ state estimation for discrete time-delayed stochastic ge...

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23rd IEEE International Conference on automation and Computing, ICAC 2017

作者： Wan, Xiongbo Wang, Zidong Ren, Chuanyu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom

ISBN: (纸本)9780701702618

This paper investigates the problem of H∞ state estimation for discrete-time stochastic genetic regulatory networks (GRNs) with switching parameters, time-varying delays, and exogenous disturbances. A new discrete-time stochastic GRN model with switching parameters is proposed by assuming that the sojourn probability of each subsystem of the GRN under consideration is known. By using the stochastic analysis approach, sufficient conditions are derived under which the augmented estimation error system is stochastically stable and satisfies a prescribed H∞ disturbance attenuation level γ. The gain matrices of the desired state estimator can be obtained by solving a matrix inequality. A numerical example is given to illustrate the effectiveness of the designed state estimator. © 2017 Chinese automation and Computing Society in the UK - CACSUK.

关键词： State estimation

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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 prediction model of edge gas flow development state based on BP neural network 5

A prediction model of edge gas flow development state based ...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhang, Jialiang An, Jianqi Wu, Min Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

The development and distribution states of the blast furnace (BF) gas flow determine whether the reaction in the furnace can proceed normally and decide the utilization efficiency of the carbon in the furnace and the stable smooth operation of the furnace. The internal environment of BF is closed with high temperature and high pressure, which causes that the relationship between the development situation of edge gas flow of the BF and the BF operation is uncertain. In this paper, a prediction model of edge gas flow development state based on BP neural network (BPNN) is proposed, clarifying the relationship between the development state of edge gas flow and the edge burden parameters. Firstly, this paper gets the relative operation factors of effecting the development situation of edge gas flow through analyzing the process mechanism of the BF ironmaking, and proposes the development index of edge gas flow and the heat load of cooling stave to measure the development state of the edge gas flow. Secondly, the intrinsic correlation between the data is verified, and the data are analyzed by Spearman's rank correlation coefficient (SRCC) analysis. Finally, according to the analysis results, combined with the burden mechanism, the edge gas flow prediction model is established to realize the prediction of the development state of the edge gas flow. The calculation of the data collected in the metallurgy scene of the BF suggested that this prediction model of the edge gas flow development state of the BF could describe the relationship between BF operation parameters and the developing state of the edge gas flow.

关键词： Flow of gases

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An Online Modeling Method for Formation Drillability Based on OS-Nadaboost-ELM Algorithm in Deep Drilling Process

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IFAC-PapersOnLine 2017年第1期50卷 12886-12891页

作者： Gan, Chao Cao, Weihua Wu, Min Chen, Xin Hu, Yule Wen, Guojun Gao, Hui Ning, Fulong Ding, Huafeng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Adavanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China School of Mechanical Engineering & Electronic Information China University of Geosciences Wuhan430074 China

To achieve safety, high quality, and efficiency in deep drilling, it is necessary to get formation drillability around the borehole during drilling-trajectory planning and intelligent drilling control. Since the drilling data have the characteristics of low value density and noise in the process of deep drilling, it is difficult to model formation drillability in deep drilling. In this paper, a new online modeling method for formation drillability based on online sequential nadaboost extreme learning machine (OS-Nadaboost-ELM) algorithm has been proposed. Firstly, the well logging parameters are chosen as the inputs of the model, whose output is formation drillability. Then, several ELM models are established and the outputs of these models are as weak learners. Then the weak learners are combined by Nadaboost algorithm in order to get a strong learner. Finally, the recursive least squares algorithm is used to adjust the model. The numerical test results show that, in both prediction accuracy and training efficiency aspects, the proposed method is better than other prediction methods such as multiple regression, gray method, back-propagation neural networks, Nadaboost extreme learning machine and online sequential extreme learning machine. Thus the prediction model serves as the online geological model to develop intelligent drilling systems. © 2017

关键词： E-learning

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