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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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Estimation of image Jacobian Matrix with time-delay compensation based on Kalman filtering with colored noise 5

Estimation of image Jacobian Matrix with time-delay compensa...

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

作者： Wang, Xinmei Liu, Zhenzhu Wei, Wu Liu, Feng School of Automation China University of Geosciences Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China College of Automation Science and Engineering South China University of Technology Guangzhou Guangdong510640 China

In order to compensate for the impact of time delay on the estimation of object feature point image and image Jacobian matrix and improve the control precision of image-based visual servo system, a Kalman filtering algorithm with colored noise is proposed to obtained the current motion state estimation of the feature point with time-delay compensation in the image space, then the accurate image Jacobian matrix under time delay can be obtained. For the above, the following work will be done in this paper: (1) the current motion state estimation of the feature point in the image space is predicted by Kalman filtering algorithm, combined with practical applications, measurement noise is usually as colored noise and can be regarded as a one-order Markov sequence excited by Gauss white noise, then a Kalman filtering recursive model can be derived according to the variance minimization principle of the estimation error;(2) to obtain the measurement vectors estimation which cannot be acquired in the Kalman filtering model owing to the existence of time delay, the relationship between the motion state of the feature point at the prior and later point is established, and a polynomial is fitted by using some of the observed data under the relationship to realize the measurement vectors estimation in the time-delay period. Thus the estimation of the motion state of the feature point at the current time in the image space can be obtained, and the estimation of image Jacobian matrix with time-delay compensation can be obtained. Experimental results validate the feasibility and superiority of this method.

关键词： Time delay

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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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Kalman and Smooth Variable Structure Filters for Pose Estimation in Robotic Visual Servoing

Kalman and Smooth Variable Structure Filters for Pose Estima...

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2017 3rd International Conference on Artificial Intelligence and Industrial engineering (AIIE2017)

作者： Xi-yuan LU Liang DU Xiao-lin REN Bo DONG Yuan-chun LI Department of Control Science and Engineering Changchun University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

Pose estimation problem of an object in real time is an important issue for robotic visual servoing(RVS). Many pose estimation schemes in RVS rely on an extended Kalman filter(EKF) that provides good accurate estimation. However, it may cause the estimation to become unstable because of nonlinear modeling uncertainties. While, smooth variable structure filter(SVSF) is a new method that is more robust to disturbances and uncertainties. In this paper, a novel pose estimate method is developed based on the EKF and SVSF. It is combined the accuracy of the EKF and the robustness provided by the SVSF that will lead to more accurate state estimates and improve robustness to modeling errors and uncertainties. The resulting algorithms are called the EKF-SVSF. The simulation results are provided to demonstrate the robustness and accuracy.

关键词： Pose estimation Robotic visual servoing(RVS) Kalman filter(KF) Smooth variable structure filter

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Neural Adaptive control of Microgrid Frequency Regulation with Wind Power

Neural Adaptive Control of Microgrid Frequency Regulation wi...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Weiqiang Liu Chaoxu Mu Ding Wang Chao Luo Chao Ren Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin China School of Automation Southeast University Nanjing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Electrical Engineering Wuhan University Wuhan China

Due to the uncertainty of power load demand and the stochastic power generation from renewable energy, frequency fluctuation becomes a major concern of power system, especially for a microgrid. In this paper, an improved proportional-integral (PI) controller based on the neural adaptive control method is proposed to deal with the load frequency control (LFC) problem in a microgrid with wind power. The designed neural adaptive control auxiliary controller is used to provide the adaptive supplement control signal to PI controller in a real-time manner. Simulation studies on a benchmark microgrid system are carried out between the proposed compound controller and traditional PI controller. The simulation results demonstrate the proposed method has a superior performance for stabilizing the frequency over the traditional PI control under disturbances from the load change and wind power.

关键词： Adaptive control Microgrids Frequency control Wind turbines Benchmark testing Power system stability

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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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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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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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Current control of IPMSM servo system in field-weakening region via DOB-based model predictive control

Current control of IPMSM servo system in field-weakening reg...

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Annual Conference of Industrial Electronics Society

作者： Chao Wu Shihua Li Qi Li Wei Xing Zheng School of Automation Southeast University Nanjing P. R. China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

Current control of IPMSM servo system is investigated in this paper. Under the field-weakening control framework, nonlinear couplings of the voltage equations are very strong. The current control performance may not be well until such nonlinear couplings are well dealed. In this case, a DOB-based model predictive control is proposed to improve the current control performance under field-weakening control framework. The proposed control method consists of a forecasted model based on disturbance observer, feedback correction for model mismatch rejection, and receding optimization for an optimized control input. Numerical simulations demonstrate that proposed method achieves nonlinear coupling attenuation ability and well promising field-weakening control performance.

关键词： Couplings Mathematical model Torque Voltage control Stators Current control

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