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第35届中国控制会议

作者： LIU Hong-Yang PENG Zhi-Hong CHEN Jie FANG Hao School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509009107

Coordinated target tracking for a team of two heterogeneous Unmanned Aerial Vehicles(UAVs) is *** order to study the coordinated relationship by means of distances of UAV-to-target and UAV-to-UAV,a constraint of distances coordination is *** from the traditional studies that focus on angular separation or communication connectivity for UAVs,this constraint takes the effect of geometric configuration for two UAVs coordination into ***,the constraint only applies to follower UAV,aiming to obtain its optimal coordinated distance to *** this way,accuracy of target state estimation and optimal geometric configuration of target tracking for UAVs are *** Information filter is used to estimate the target location on a 2-D plane,and a receding horizon approach is applied to generate the optimal control policy for two UAVs' *** results illustrated the effectiveness.

关键词： UAVs target tracking state estimation constraint of distances coordination

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Multi-sensor optimal distributed weighted Kalman filter fusion over unreliable networks 35

Multi-sensor optimal distributed weighted Kalman filter fusi...

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第35届中国控制会议

作者： XING Zirui XIA Yuqing Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509009107

This paper presents the problem of optimal distributed weighted Kalman filter fusion for a class of multi-sensor unreliable networked systems with uncorrelated *** distributed multi-sensor data fusion system suffers measurements delay or loss due to unreliability of networked systems with uncorrelated *** the addressed model,an optimal local Kalman filter with a finite buffer is derived for each subsystem,which can also be used as a centralized optimal Kalman filter fusion *** on the new optimal local Kalman filter,multi-sensor optimal distributed weighted Kalman filter fusion with finite buffers has been ***,compared with the centralized optimal Kalman filter fusion algorithm,the proposed distributed weighted Kalman filter fusion algorithm developed in this paper has stronger fault-tolerance *** results are provided to illustrate the effectiveness of the proposed approaches.

关键词： Multi-sensor unreliable networked systems Distributed weighted Kalman filter fusion Network delay Buffers

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The Forecasting Research on the Model of the Hysteresis Brake based on Elman Multi-Hidden Layers Neural Network Algorithm with the Speed and Directional Factor 35

The Forecasting Research on the Model of the Hysteresis Brak...

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第35届中国控制会议

作者： ZHANG Bo SHEN Wei WANG Junzheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509009107

Hysteresis brake,which provides for step-less torque and high speed,is a stable and reliable device used for loading,but with some problems,such as the large time-lag,strong nonlinearity,and difficulty in modeling et *** to the above-mentioned issues,the special working conditions of hysteresis brake developed by our project team and the advantage of the dynamical performance of the Elman Multi-Hidden Layers Neural Network,this paper employs modified neural network algorithm with Elman dynamic recursive structure to accomplish the model of hysteresis brake,and guarantees the accuracy of output loaded *** this algorithm,we introduce the speed,the given and desired torque,and a directivity factor respectively as a disturbance variable and two input vectors of the system,and then train the model and *** numerical results validate the effectiveness of the algorithm proposed.

关键词： Hysteresis brake strong nonlinearity neural network algorithm with Elman dynamic recursive structure

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Semantic motion segmentation for urban dynamic scene understanding

Semantic motion segmentation for urban dynamic scene underst...

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2016 IEEE International Conference on automation Science and Engineering, CASE 2016

作者： Fan, Qiu Yi, Yang Hao, Li Mengyin, Fu Shunting, Wang School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509024094

A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status for each pixel of images. First, we extract and match sparse image features to estimate ego-motion between two consecutive stereo images, the result of feature points grouping is used to segment moving object in U-disparity map. Second, a Fully Convolutional Neural Network is employed for semantic segmentation. Moreover, semantic cues are utilized to remove pixels have no potential to be moved in motion mask. Finally, we use a fully connected CRF to integrate motion into semantic segmentation. To validate the effectiveness of the proposed algorithm, we present experimental results with KITTI stereo images that contain moving objects. © 2016 IEEE.

关键词： Semantics

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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TIEA: A tradeoff-based interactive multiobjective evolutionary algorithm 7

TIEA: A tradeoff-based interactive multiobjective evolutiona...

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7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016

作者： Chen, Lu Xin, Bin Chen, Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9784990534349

This paper proposes a tradeoff based interactive multiobjective evolutionary algorithm (TIEA). It can support the decision maker (DM) to guide the search towards the DM's most preferred solution by combing evolutionary algorithms with the framework of gradient projection. At each iteration, an evolutionary algorithm is used to generate an approximate Pareto optimal solution. Then, the DM is asked to provide preferences in terms of indifference tradeoffs, the projection of which onto the tangent hyperplane of the Pareto front provides a tradeoff direction. To calculate the projection, an approach to approximate the normal vector of the tangent hyperplane of the Pareto front is developed. Results on nine numerical examples by using TIEA show that TIEA is able to solve multiobjective optimization problems with more than three objectives. Moreover, it can find the Pareto optimal solution that the DM prefers most. © 2016, Fuji Technology Press. All rights reserved.

关键词： Evolutionary algorithms

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New advances in complex motion control for single robot systems and multi-agent systems

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Science China(Technological Sciences) 2016年第12期59卷 1963-1964页

作者： FANG Hao LU Shao Lei CHEN Jie School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China

CHEN Jie,email：chenjie@***

关键词： robot advances email cooperation simplified decomposed scenarios classic climbing obstacles

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Maximum power point tracking control of direct-drive permanent magnet wind turbine based on adaptive neuro-fuzzy inference system 5

Maximum power point tracking control of direct-drive permane...

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

作者： Ding, Min Ou, Yingxiong Hu, Bo She, Jinhua Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China State Grid Energy Research Institute Beijing102200 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

The power from wind varies depending on the environmental factors. Because of the randomness and intermittent of wind, it is difficult for the wind energy conversion system to locate and track the maximum power point (MPP) with fast speed and high accuracy under the condition of variable wind speed. In this paper, a variable-speed wind-generator maximum power point tracking (MPPT) control method based on adaptative neuro-fuzzy inference system (ANFIS) is presented. It is designed as a combination of the Sugeno fuzzy model and neural network. The ANFIS based controller predicts the optimum speed with the inputs as the speed change and power change, and controls the speed with PI controllers. The performance of the proposed controller is tested for direct-drive permanent magnet wind turbine based wind energy conversion system under fast wind speed variation in MATLAB/Simulink. The simulation results show that the designed control method has good dynamic characteristics and steady-state accuracy in wind power MPPT and improves the working efficiency.

关键词： Wind turbines

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Solutions Verification for Cloud-Based Networked control system using Karush-Kuhn-Tucker Conditions

Solutions Verification for Cloud-Based Networked Control Sys...

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Chinese automation Congress

作者： Yasir Ali Zhen Shen Fenghua Zhu Gang Xiong Shichao Chen Yuanqing Xia Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automation Beijing Institute of Technology China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

The rapid development of the Cloud Computing Technologies (CCTs) has amended the conventional design of resource-constrained Network control system (NCS) to the powerful and flexible design of Cloud-Based Networked control system (CB-NCS) by relocating the processing part to the cloud server. This arrangement has produced many internets based exquisite applications. However, this new arrangement has also raised many network security challenges for the cloud-based control system related to cyber-physical part of the system. In the absence of robust verification methodology, an attacker can launch the modification attack in order to destabilize or take control of NCS. It is desirable that there shall be a solution authentication methodology used to verify whether the incoming solutions are coming from the cloud or not. This paper proposes a methodology used for the verification of the receiving solution to the local control system from the cloud using Karush-Kuhn-Tucker (KKT) conditions, which is then applied to actuator after verification and thus ensure the stability in case of modification attack.

关键词： Cloud-based control system Security of NCS Analysis of solution verification for NCS KKT conditions

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Compressive phase retrieval via reweighted amplitude flow

arXiv

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arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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