检索结果-内蒙古大学图书馆

第35届中国控制会议

作者： CHEN Yang-Yang TIAN Yu-Ping WANG Zan-Zan School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

ISBN: (纸本)9781509009107

This paper deals with cooperative estimation and control for second-order agents formation tracking a set of given orbit in an external flowfield,where only direction of flow inertial velocity is spatiotemporal and known.A novel coordinated adaptive estimator based on local neighbor-to-neighbor information is proposed to estimate the flow *** is shown that our previous geometric extension design,consensus and adaptive backstepping method can be combined together to construct the robust formation tracking controller under bidirectional *** theoretical result is proved by the numerical simulation.

关键词： Coordinated Adaptive Estimation Second-Order Agents Formation Tracking control

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GPIO based backstepping control for electronic throttle

GPIO based backstepping control for electronic throttle

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Annual Conference of Industrial Electronics Society

作者： Ke Shi Zuo Wang Chao Wu Shihua Li Senior Member IEEE School of Automation Southeast University Nanjing PR China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering PR China

This paper mainly studies the angle tracking problem in electronic throttle system with unknown time-varying disturbances. Firstly, generalized proportional integral observer (GPIO) is used to estimate the time-varying disturbances including model uncertainties, friction torque and spring initial torque. Secondly, a composite controller combining disturbance estimation and backstepping control method is designed, which is called the BSC+GPIO method. This control method is convenient to implement and the disturbance rejection capability is enhanced by feedforward compensating the estimated value of system disturbances. The simulation results show the effectiveness of the proposed method.

关键词： Torque Observers DC motors Friction Backstepping Springs

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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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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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Feature fusion methods for robust speech emotion recognition based on deep belief networks 16

Feature fusion methods for robust speech emotion recognition...

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5th International Conference on Network, Communication and Computing, ICNCC 2016

作者： Wu, Ao Huang, Yongming Zhang, Guobao Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450347938

The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of SNR (Signal to Noise Ratio) of speech signals. In this paper, we propose novel sub-band spectral centroid weighted wavelet packet cepstral coefficients (W-WPCC) for robust speech emotion recognition. The W-WPCC feature is computed by combining the sub-band energies with sub-band spectral centroids via a weighting scheme to generate noise-robust acoustic features. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The welltrained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. We extracted prosody feature, voice quality features and wavelet packet cepstral coefficients (WPCC) from the speech signals to combine with W-WPCC and fused them by Deep Belief Networks (DBNs). Experimental results on Berlin emotional speech database show that the proposed fused feature with W-WPCC is more suitable in speech emotion recognition under noisy conditions than other acoustics features and proposed DBNs feature learning structure combined with W-WPCC improve emotion recognition performance over the conventional emotion recognition method. © 2016 ACM.

关键词： Emotion Recognition

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Global output feedback stabilization for a class of nonlinear time-delay systems via linear sampled-data control 31

Global output feedback stabilization for a class of nonlinea...

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31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016

作者： Wang, Pan Chai, Lin Fei, Shumin School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9781509044238

This thesis researches the problem of global stabilization via output feedback by using linear sampled data controller for a family of nonlinear time-delay systems which satisfy a linear growth condition. Firstly, an inductive approach is proposed to estimate the state growth in nonlinear time-delay systems. Secondly, in the condition of just the output is measurable, a linear sampled data controller via output feedback with a scaling gain is designed by means of output domination method. Finally, the scaling gain which is a positive constant and a appropriate sampling period are determined to stabilize the closed-loop system asymptotically. © 2016 IEEE.

关键词： Closed loop systems

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Local super-ellipsoid formation tracking control for first-order agents with an unknown moving target

Local super-ellipsoid formation tracking control for first-o...

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Chinese Automation Congress (CAC)

作者： Yang-Yang Chen Hao Sun Tailai Lin Qingling Wang Ya Zhang Junyu Zha Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing P.R. China School of Automation Southeast University Nanjing P.R. China

ISBN: (纸本)9781538635254;9781538635247

This paper addresses a local formation tracking control for multiple first-order agents in 3D space, where each agent's trajectory converges to the given super-ellipsoid and the tracking target is movement with an unknown speed. Differing from the using of GPS in the literature, a new distributed solution is given based on local measurements of relative position. To develop the spherical formation tracking motion into the superellipsoidal case, a general desired distance function of the relative position is introduced to describe the super-ellipsoidal following error and each agent's control input projected onto the superellipsoidal normal vector service to super-ellipsoidal following. At the same time, each agent's control input projected onto the the direction of meridian and parallel are used to accomplish the solid formation along meridian and parallel. Λ consensus-based estimator is given to estimate the moving target's speed according to adaptive design. The validity of the proposed control law is proved through numerical simulations.

关键词： Target tracking Sea measurements Extraterrestrial measurements Topology Three-dimensional displays Oceans

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An effective vehicle logo recognition method for road surveillance images 2

An effective vehicle logo recognition method for road survei...

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2nd IEEE International Conference on Computer and Communications, ICCC 2016

作者： Chen, Cong Lu, Xiaobo Shengqin, Jiang Jiaji, Song School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781467390262

In this paper, an improved vehicle logo recognition method is proposed for detecting and recognizing logo in images captured by road surveillance cameras. Firstly, a feature-match based symmetry detection algorithm is adopted for detecting symmetric axis in the image and rotating the image. Then a learning-based License Plate Localization (LPL) approach and a coarse logo location algorithm by using prior knowledge are used to obtain a coarse logo region. Moreover, a new vehicle logo location method based on Gabor Filters is put forward in order to localize the exact region of logo. In addition, two features - Pyramid of Histograms of Orientation Gradients (PHOG) and Multi-scale Block Local Ternary Patterns (MB-LTP) are combined to recognize the vehicle logo. At last, experimental results on a large number of images validate the robustness and efficiency of the proposed algorithm. © 2016 IEEE.

关键词： Gabor filters

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Finite-time output consensus of second-order multi-agent systems with mismatched disturbances via active anti-disturbance control

Finite-time output consensus of second-order multi-agent sys...

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Asian control Conference

作者： Guipu Li Xiangyu Wang Shihua Li Wei Xing Zheng Xisong Chen School of Automation Southeast University Nanjing PR China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education PR China School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

ISBN: (纸本)9781509015740;9781509015733

This paper studies the finite-time output consensus problem of second-order multi-agent systems with both mismatched disturbances and unknown state elements. This problem is solved by an active anti-disturbance control (AADC) method, which integrates the disturbance estimation/compensation and the baseline consensus protocols based on feedback control together. To estimate the matched/mismatched disturbances and the agents unknown state elements, a finite-time generalized state observer is constructed for each agent. Based on the distributed adding a power integrator feedback control method, and the estimates of the matched/mismatched disturbances and the systems unknown states, AADC consensus protocols are developed for both leaderless and leader-follower cases. The proposed protocols achieve finite-time consensus of the agents outputs in both cases. Simulation results demonstrate the effectiveness of the proposed consensus algorithms.

关键词： Multi-agent systems Output consensus Mismatched disturbances Distributed adding a power integrator method Finite-time generalized state observer

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