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Chinese control Conference (CCC)

作者： Nsubuga Latifu Zhuoyue Song Chao Duan Zhen Li Housheng Su Qinghe Wu Xiangdong Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China School of Automation Huazhong University of Science and Technology Wuhan People's Republic of China

This paper investigates a distributed finite-time attitude synchronization and tracking problem of multiple spacecraft when a time varying reference signal is available to only a subset of group members. Modified Rodrigues parameters are used for attitude representation. A two layer sliding mode surface with fast non-singular terminal sliding mode surface (FNTSMS) as the inner layer and terminal sliding mode surface (TSMS) as the outer layer is used to create a full order sliding mode surface. The proposed distributed attitude coordination control law guarantees attitude synchronization and tracking as long as their exists atleast one spacecraft that has a direct access to the virtual leader's time varying attitude. Finite-time stability of the closed loop system is guaranteed by Lyapunov-based stability method. Simulation results are presented to validate the performance of the proposed control strategy.

关键词： Space vehicles Attitude control Synchronization Sliding mode control Decentralized control Symmetric matrices Stability analysis

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State Estimation and Fault Detection for Nonlinear Dynamic systems

State Estimation and Fault Detection for Nonlinear Dynamic S...

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Chinese control Conference (CCC)

作者： Baohua Lu Liping Yan Hongxue Chen Yuanqing Xia Mengyin Fu Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In practical problems, the dynamic systems are usually nonlinear. In this case, the traditional Kalman filter cannot be used for state estimation or fault detection. The two typical extension based on Kalman filtering framework is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Theoretically speaking, UKF is better than EKF when estimation accuracy is concerned, especially for high degree nonlinear cases. This paper is concerned with the state estimation and fault detection problem for a class of nonlinear dynamic systems. A novel fault detection and analyse method is presented based on the period residual of EKF and UKF. For different kind of faults, mainly, the system parameter error, the sensor/data error, EKF and UKF are used and the estimation and fault detection effects are compared and analyzed.

关键词： Fault detection Mathematical model State estimation Kalman filters Nonlinear systems Jacobian matrices

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Distributed Algorithm for Discrete-Time Lyapunov Equations

Distributed Algorithm for Discrete-Time Lyapunov Equations

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International Conference on control, automation, Robotics and Vision

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Ministry of Education Beijing Institute of Technology Beijing China

This paper investigates the problem of solving a unique solution to discrete-time Lyapunov equations (DTLE) using multi-agent networks. We propose a distributed algorithm where each agent only uses partial information of the matrices. The agents of the algorithm reach a consensus by exchanging information with their neighbors over an undirected connected graph. We provide convergence analysis and the convergence rate estimate for the proposed algorithm. Finally, convergence performance is verified by numerical simulations.

关键词： Distributed algorithms Mathematical model Convergence Optimization Radio frequency Convex functions Symmetric matrices

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Crowdsensing game with demand uncertainties: A deep reinforcement learning approach

arXiv

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arXiv 2018年

作者： Zhan, Yufeng Xia, Yuanqing Zhang, Jiang Li, Ting Wang, Yu School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Lab Department of Computer Science University of North Carolina at Charlotte CharlotteNC28223 United States

Currently, explosive increase of smartphones with powerful built-in sensors such as GPS, accelerometers, gyroscopes and cameras has made the design of crowdsensing applications possible, which create a new interface between human beings and life environment. Until now, various mobile crowdsensing applications have been designed, where the crowdsourcers can employ mobile users (MUs) to complete the required sensing tasks. In this paper, emerging learning-based techniques are leveraged to address crowdsensing game with demand uncertainties and private information protection of MUs. Firstly, a novel economic model for mobile crowdsensing is designed, which takes MUs' resources constraints and demand uncertainties into consideration. Secondly, an incentive mechanism based on Stackelberg game is provided, where the sensing-platform (SP) is the leader and the MUs are the followers. Then, the existence and uniqueness of the Stackelberg Equilibrium (SE) is proven and the procedure for computing the SE is given. Furthermore, a dynamic incentive mechanism (DIM) based on deep reinforcement learning (DRL) approach is investigated without knowing the private information of the MUs. It enables the SP to learn the optimal pricing strategy directly from game experience without any prior knowledge about MUs' information. Finally, numerical simulations are implemented to evaluate the performance and theoretical properties of the proposed mechanism and approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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Construction of Barrier in a Fishing Game with Point Capture

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IEEE Transactions on Cybernetics 2017年第6期47卷 1409-1422页

作者： Zha, Wenzhong Chen, Jie Peng, Zhihong Gu, Dongbing School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom

This paper addresses a particular pursuit-evasion game, called as 'fishing game' where a faster evader attempts to pass the gap between two pursuers. We are concerned with the conditions under which the evader or pursuers can win the game. This is a game of kind in which an essential aspect, barrier, separates the state space into disjoint parts associated with each player's winning region. We present a method of explicit policy to construct the barrier. This method divides the fishing game into two subgames related to the included angle and the relative distances between the evader and the pursuers, respectively, and then analyzes the possibility of capture or escape for each subgame to ascertain the analytical forms of the barrier. Furthermore, we fuse the games of kind and degree by solving the optimal control strategies in the minimum time for each player when the initial state lies in their winning regions. Along with the optimal strategies, the trajectories of the players are delineated and the upper bounds of their winning times are also derived. © 2013 IEEE.

关键词： Optimal systems

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Synchronization Tracking of Heterogeneous Robotic systems with Parametric Uncertainties and Communication Delays 5

Synchronization Tracking of Heterogeneous Robotic Systems wi...

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5th International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2018

作者： Yao, Xiang-Yu Ge, Ming-Feng Ding, Hua-Feng Wang, Leimin Liu, Jie Han, Tao Liu, Zhi-Wei School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Huazhong University of Science and Technology Wuhan430074 China School of Hydropower and Information Engineering Huazhong University of Science and Technology Wuhan430074 China College of Mechatronics and Control Engineering Hubei Normal University Huangshi435002 China School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781538670880

This paper studies synchronization tracking problems of heterogeneous robotic systems in the presence of kinematic uncertainties, dynamic uncertainties and communication delays. To solve the above problems, this paper develops cooperative adaptive controllers based on directed topologies containing spanning trees, which relaxes the constraints on communications than the previous works with undirected or strongly connected topologies. By invoking Lyapunov stability and Input-output stability techniques, sufficient criteria for asymptotical stability of the systems are obtained. Moreover, the obtained results are expanded to formation problems in similar cases. Finally, the validity of the theoretical results and the numerical comparisons with existing work are supported by numerous simulations. © 2018 IEEE.

关键词： Topology

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Curved path planning based on 3D vision water immersion ultrasonic nondestructive testing

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Journal of Physics: Conference Series 2021年第1期2024卷

作者： Zheng Chen Jian Wang Hualiang Zhang School of Information Engineering Shenyang University of Chemical Technology Shenyang Liaoning 110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Liaoning 110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning 110169 China

Compared with traditional 2D image processing, 3D point cloud processing has become a hot technology in the industry, but there are few researches applied to nondestructive testing of curved workpieces. This article aims at the non-destructive testing of curved workpieces, using 3D point cloud and robotic arm for water immersion ultrasonic non-destructive testing. Aiming at the 3D point cloud with many outliers, using the commonly used filter in two-dimensional images-the guide filter, the algorithm is improved and used for the filtering and downsampling of the 3D point cloud, and the adjustment of the curved surface workpiece and the robot arm's pose is introduced. Finally, the workpiece was scanned by a robotic arm with a water immersion ultrasonic nondestructive testing system to prove the feasibility of the experiment and improve the detection efficiency of traditional nondestructive testing technology.

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Analysis of Influencing Factors on Carbon Monoxide Utilization Rate of Blast Furnace Based on Multi-Timescale Characteristics 36

Analysis of Influencing Factors on Carbon Monoxide Utilizati...

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第36届中国控制会议

作者： Jianqi An Yuwan Yang Min Wu Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Computer Science School of ComputingTokyo Institute of Technology

ISBN: (纸本)9781538629185

In the blast furnace,due to the different changing frequency of different operations,and the different reaction time of gas,liquid and solid materials,there exists multi-timescale characteristics in the iron-making ***,not enough attention has been paid to this characteristic,most of the analyses on the blast furnace state before are under a fixed time ***,this paper makes a analysis of influencing factors on carbon monoxide utilization rate of blast furnace based on multi-timescale ***,the factors that affect the carbon monoxide utilization rate are analyzed from different time ***,in the short time scale,the individual influencing time scale of the permeability index,total pressure difference and top temperature is found by the support vector machine（SVM） *** in the long time scale,the influencing time scale of burdening is *** the validity of each model is verified by the field data of the blast furnace.

关键词： Multi-time scales Carbon monoxide utilization Support vector machine Blast furnace

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PDP: Parallel Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 1-5页

作者： Fei-Yue Wang Jie Zhang Qinglai Wei Xinhu Zheng Li Li IEEE State Key Laboratory of Management and Control for Complex Systems(SKL-MCCS) Institute of AutomationChinese Academy of Sciences(CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Department of Computer Science and Engineering University of Minnesota Department of Automation Tsinghua University

Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive dynamic programming ADP is first presented instead of direct dynamic programming DP , and the inherent relationship between ADP and deep reinforcement learning is developed. Next, analytics intelligence, as the necessary requirement, for the real reinforcement learning, is discussed. Finally, the principle of the parallel dynamic programming, which integrates dynamic programming and analytics intelligence, is presented as the future computational intelligence. © 2014 Chinese Association of automation.

关键词： Artificial intelligence Neural networks Reinforcement learning

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Robust Iterative Learning control for Alloy Batch Weighing Process in Refining Furnace 36

Robust Iterative Learning Control for Alloy Batch Weighing P...

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第36届中国控制会议

作者： Yibo Huang Jianqi An Yong He Min Wu Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Computer Science School of ComputingTokyo Institute of Technology

ISBN: (纸本)9781538629185

This paper proposes a robust iterative learning control method for the refining furnace alloy weighing process to solve the problem of the poor control accuracy and stability caused by the changing of alloy properties and the frequency of the vibration feeder. First, a two dimensional（2D） weighing model was established based on the analysis of the dynamic characteristics of alloy weighing process. Second, a control scheme is proposed for the 2D model of alloy weighing ***, a robust iterative learning controller is developed and a stability condition of the 2D system is derived through linear matrix inequality（LMI） obtained by a 2D Lyapunov-Krasovskii function. Finally, the simulation results show that the proposed method can sufficiently improve the control precision of the alloy weighing process.

关键词： Iterative learning control 2D weighing model Batch process Alloy weighing process Robust control

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