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24th International Conference on Neural Information Processing, ICONIP 2017

作者： Dong, Bo Liu, Keping Li, Hui Li, Yuanchun Department of Control Science and Engineering Changchun University of Technology Yan’an Avenue. 2055 Changchun130012 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Zhongguancun East Road. 95 Beijing100190 China

ISBN: (纸本)9783319701356

This paper presents a novel decentralized control approach for modular and reconfigurable robots (MRRs) with uncertain environment contact under a learning-based optimal compensation strategy. Unlike the known optimal control methods that are merely suitable for specific classes of robotic systems without implementing dynamic compensations, in this investigation, the dynamic model of the MRR system is described as a synthesis of interconnected subsystems, in which the obtainable local dynamic information is utilized effectively to construct the feedback controller, thus making the decentralized optimal control problem of the MRR system be formulated as an optimal compensation issue of the model uncertainty. A policy iteration algorithm is employed to solve the Hamilton-Jacobi-Bellman (HJB) equation with a modified cost function, which is approximated by constructing a critic neural network, and then the approximate optimal control policy can be derived. The asymptotic stability of the closed-loop MRR system is proved by using the Lyapunov theory. At last, simulations are performed to verify the effectiveness of the proposed decentralized optimal control approach. © Springer International Publishing AG 2017.

关键词： Neural networks

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Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

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Chinese control Conference

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O. Wang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Chongqing China Department of Mechanical Engineering Boston University Boston MA USA

The network structure and functional properties of gene regulatory system and their relationships arc an important research field in systems biology. In this paper, a new improved model is proposed based on the study of gene expression process. The model takes into account the effect of protein concentration on the gene expression, so as to obtain a new bifurcation point and improve the performance of the system. The validity of the model is verified by theoretical analysis and data simulation.

关键词： Mathematical model Proteins Stability analysis Bifurcation Biological system modeling Delays RNA

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Effect of leakage delay on Hopf bifurcation in a fractional BAM neural network

arXiv

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arXiv 2018年

作者： Lin, Jiazhe Xu, Rui Li, Liangchen Tian, Xiaohong Institute of Applied Mathematics Army Engineering University ShijiazhuangHebei050003 China Complex Systems Research Center Shanxi University Taiyuan Shanxi030006 China Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Shanxi University Taiyuan Shanxi030006 China

Recently, the influence of leakage delay on the dynamics of integer-order neural networks has been investigated extensively. It has been confirmed that fractional calculus can depict the memory and hereditary attributes of neural networks more accurately. In this paper, we study the existence of Hopf bifurcation in a six-neuron fractional bidirectional associative memory (BAM) neural network with leakage delay. By selecting two appropriate bifurcation parameters and analyzing corresponding characteristic equations, it is verified that the delayed fractional neural network generates a Hopf bifurcation when the bifurcation parameters pass through some critical values. In order to measure how much impact of leakage delay on Hopf bifurcation, sensitivity analysis methods, such as scatter plots and partial rank correlation coefficients (PRCCs), are introduced to assess the sensitivity of bifurcation amplitudes to leakage delay. Numerical examples are carried out to illustrate the theoretical results and help us gain an insight into the effect of leakage delay vividly. Copyright © 2018, The Authors. All rights reserved.

关键词： Sensitivity analysis

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Single Image Depth Level Estimation Using Dark Channel Prior

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IOP Conference Series: Materials Science and engineering 2018年第1期435卷

作者： Yichao Cao Xiaobo Lu School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China

In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in the image poses a huge challenge for smoke detection and other video analysis tasks. Appropriate depth level estimation provide significant prior knowledge for subsequent identification and detection. For landscape images, we can approximate the air transmittance to depth information for histogram analysis. The depth value is segmented by a multi-threshold segmentation algorithm, and the resulting image can be used for forest fireworks detection and the like. This method does not rely on samples and classifiers, and the algorithm does not require training. The final experimental results show that the depth level estimation of a single landscape image based on the dark channel prior can achieve good results.

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A Deep Learning Approach for Face Detection and Location on Highway

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IOP Conference Series: Materials Science and engineering 2018年第1期435卷

作者： Yang Zhang Peihua Lv Xiaobo Lu School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China

Face detection and location technique is a hot research direction during recent years. Especially, driver face detection on highway is still a challenging problem in social safty deserving research. This paper proposes a novel algorithm based on the improved Multi-task Cascaded Convolutional Networks (MTCNN) and Support Vector Machine (SVM) to realize accurate face region detection and feature location of driver's face on highway, predicting face and feature location via a coarse-to-fine pattern. The proposed algorithm is verified under various complex highway conditions. Experimental results show that the proposed model shows satisfied performance compared to other state-of-the-art techniques used in driver face detection and alignment, keeping robust to the occlusions, varying pose and extreme illumination on highway.

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Dual refinement networks for accurate and fast object detection in real-world scenes

arXiv

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arXiv 2018年

作者： Chen, Xingyu Yu, Junzhi Kong, Shihan Wu, Zhengxing Wen, Li State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 University of Chinese Academy of Sciences Beijing100049 China Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing100871 China School of Mechanical Engineering and Automation Beihang University Beijing100191 China

Object detection has been vigorously studied for years but fast accurate detection for real-world scenes remains a very challenging problem. Overcoming drawbacks of singlestage detectors, we take aim at precisely detecting objects for static and temporal scenes in real time. Firstly, as a dual refinement mechanism, a novel anchor-offset detection including an anchor refinement, a feature offset refinement, and a deformable detection head is designed for two-step regression and capture of accurate detection features. Based on the anchoroffset detection, a dual refinement network (DRN) is developed for high-performance static detection, where a multi-deformable head is further designed to leverage contextual information for describing objects. As for temporal detection in real-world scenes, temporal refinement networks (TRN) and temporal dual refinement networks (TDRN) are developed by propagating the refinement information across time, where we also propose a loose refinement strategy to match object motion with the previous refinement. Our proposed methods are evaluated on PASCAL VOC, COCO, and ImageNet VID datasets. Extensive comparison on static and temporal detection verify the superiority of DRN, TRN, and TDRN. Consequently, our developed approaches run in a fairly fast speed, and in the meantime achieve a significantly enhanced detection accuracy, i.e., a mAP of 82.8% on VOC 2007, 80.6% on VOC 2012, 69.4% on VID 2017, and an AP of 34.3% on COCO. Ultimately, producing encouraging results, our methods are applied to underwater object grasping with an autonomous system. Codes are publicly available at http://***/SeanChenxy/TDRN. Copyright © 2018, The Authors. All rights reserved.

关键词： Computer vision

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Active damping of a DC network with a constant power load: An adaptive passivity-based control approach

arXiv

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arXiv 2018年

作者： Machado, Juan E. Arocas-Pérez, José He, Wei Ortega, Romeo Griñó, Robert Laboratoire des Signaux et Systèmes CNRS-Supélec Plateau du Moulon91192 France Universitat Politècnica de Catalunya Barcelona08028 Spain Key Laboratory of Measurements and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

This paper proposes a nonlinear, adaptive controller to increase the stability margin of a direct-current (DC) small-scale electrical network containing a constant power load, whose value is unknown. Due to their negative incremental impedance, constant power loads are known to reduce the effective damping of a network, leading to voltage oscillations and even to network collapse. To tackle this problem, we consider the incorporation of a controlled DC-DC power converter between the feeder and the constant power load. The design of the control law for the converter is based on the use of standard Passivity-Based control and Immersion and Invariance theories. The good performance of the controller is evaluated with numerical simulations. Copyright © 2018, The Authors. All rights reserved.

关键词： Adaptive control systems

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Adaptive Vi Be background model for vehicle detection

Adaptive Vi Be background model for vehicle detection

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Chengyi Pan Zhou Zhu Liangwei Jiang Min Wang Xiaobo Lu School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing University of Science & Technology Key Laboratory of Ministry of Public Security for Road Traffic Safety

Background extraction is an important step in vehicle detection. In the actual scene, change of illumination will lead to a tremendous background change. It is necessary to update the background model

ISBN: (纸本)9781467389808

关键词： Background ViBe Adaptive Error function Evaluation conditions Vehicle detection Vehicle detection ERROR FUNCTIONS Self tuning BACKGROUND illumination Lighting

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Weighted Consensus of Multi-Agent systems Using both Time-delay State and Current State 35

Weighted Consensus of Multi-Agent Systems Using both Time-de...

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第35届中国控制会议

作者： He Ying-gao Wang Xiang-yu Wuxi Institute of Arts & Technology School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (纸本)9781509009107

This paper investigates consensus of continuous-time multi-agent system through adjusting the proportion of the current state and time-delay state in the control algorithm,supposing that its topology is fixed and a directed interconnection graph which contains a spanning tree.A sufficient condition for the convergence to a consensus is proposed and proved based on the generalized Nyquist stability criterion and the Gerschgorin disk theorem.A method is found to enlarge upper bound on the maximum time-delay,numerical simulations are shown to demonstrate the validity of the achieved theoretical results.

关键词： multi-agent system weighted consensus Nyquist criterion Gerschgorin disk theorem

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An SNR-Adaptive Relaying Algorithm for Multi-Antenna Cooperative Networks

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China Communications 2017年第10期14卷 228-236页

作者： Shuangshuang Han Peng Zhang Feijin Shi Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing China Qingdao Academy of Intelligent Industries Qingdao Shandong Province China The School of Computer Engineering Weifang University Shandong P. R. China Communications Headquarters Ministry of Foreign Affairs of the People's Republic of China Beijing China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha China

Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward(AF) and decode-and-forward(DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio(SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward(SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.

关键词： MIMO SNR SNR-adaptive forward multi-antenna

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