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IEEE International Conference on Robotics and Biomimetics

作者： Fan Yang Zeng-Guang Hou Shao-Hua Mi Gui-Bin Bian Xiao-Liang Xie State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479927456

The visualization of the coronary vasculature is of utmost importance in interventional cardiology. Intravascular surgical robots assist the practitioners to perform the complex procedure while protecting them from the tremendous occupational hazards. Robotic surgical simulation aims to provide support for the learners in both efficiency and convenience. The blood vessels especially the coronary arteries with rich details are the key part of the anatomic scenario of the virtual training system. The variations in diameters and directions make the segmentation of the coronary arteries a difficult work. In this paper, a robust and semi-automatic approach for the segmentation of the coronary arteries is developed. The approach is based on the multi-scale tubular enhancement and an improved geodesic active contours model. The demonstrated approach firstly enhances the tubular objects by computing their “vesselness”. Next the edge potential maps are calculated based on the enhanced information. Meanwhile, the initial contours are generated by a modified fast marching method. Then the actual wave fronts evolution extracts the details of the coronary arteries. Finally the visualization model is organized based on the segmentation results by the marching cubes method. This approach has been proved successful for the visualization of the coronary arteries based on the CTA information.

关键词： Arteries Robots Computational modeling Level set Eigenvalues and eigenfunctions Visualization Training

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EMG-based Estimation of Knee Joint Angle under Functional Electrical Stimulation Using an Artificial Neural Network

EMG-based Estimation of Knee Joint Angle under Functional El...

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第三十二届中国控制会议

作者： Yixiong Chen Jin Hu Feng Zhang Pengfeng Li Zengguang Hou State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781479900305

In this paper,an artificial neural network is proposed to estimate knee joint angle in hybrid activation of knee extension motion,including voluntary muscle contraction and functional electrical stimulation(FES) induced *** electromyography(EMG) signals of three muscles responsible for knee extension and FES parameter which describe the FES intensity are used as input vector of the neural network,while the estimated knee angle is the *** the experiment, FES with different combinations of parameters(pulse amplitude and pulse width) was delivered to the rectus femoris muscle of a healthy male subject when the knee was in a periodic extension motion by voluntary muscle *** EMG signals of three muscles,parameters of FES as well as the actual knee angle were ***,there were 52,233 and 17,420 sampling points corresponding to 261 and 87 seconds used to train and validate the neural *** result shows the trained network has a satisfactory performance on knee joint angle estimation whose output well follows the curve of actual knee angle. Root mean square error between estimated angle and actual angle is employed to represent the estimation accuracy which is 5.07 degree according to the experimental data.

关键词： Functional electrical stimulation Electromyography Neural network

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Predicting User Participation in Social Networking Sites

Predicting User Participation in Social Networking Sites

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IEEE International Conference on Intelligence and Security Informatics

作者： Qingchao Kong Wenji Mao Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467362146

Social networking sites provide a convenient way for users to participate in discussion groups and communicate with others. While users situate in and enjoy such a social environment, it is important for various security related applications to understand, model and analyze participating users' behavior. In this paper, we make an attempt to model and predict user participation behavior in discussion groups of social networking sites. Our work employs a feature-based approach, which considers four types of features: thread features, content similarity, user behavior and social features. We conduct an empirical study on a popular social networking site in China, ***. The experimental results show the effectiveness of our approach.

关键词： User participation Behavior modeling and prediction Social networking sites

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Task-oriented active training based on adaptive impedance control with iLeg — A horizontal exoskeleton for lower limb rehabilitation

Task-oriented active training based on adaptive impedance co...

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IEEE International Conference on Robotics and Biomimetics

作者： Jin Hu Zeng-Guang Hou Yixiong Chen Liang Peng Long Peng State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479927456

A horizontal exoskeleton for lower limb rehabilitation called iLeg has been developed by our laboratory which consists of two 3-DOF (degrees of freedom) robotic leg orthoses. This paper proposes a position-based impedance control with the compensation of BP NNs (back propagation neural networks) for the exoskeleton. Based on the control scheme, the task-oriented active training is investigated where impedance parameters are self-adjusted to movement deviation and patient activities with fuzzy logic. An adaptive haptic interface of active compliance is ensured to provide positive feedback to patients when their effort is desired or negative otherwise, which encourages patients to practice the desired movement following the predefined directed path. Besides, the timing freedom is separated from spatial trajectory and determined by patients. Voluntary effort hence becomes a requirement during the exercises, no effort no movement, so that active contribution of patients is highly motivated. Simulation results have verified the feasibility of the control scheme and the training strategy. An active compliant environment is created with adaptive haptic interface for task-oriented patient-driven training of multi-joint coordination.

关键词： Training Impedance Vectors Joints Robot kinematics Artificial neural networks

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Distributed adaptive sliding mode control for attitude tracking of multiple spacecraft

Distributed adaptive sliding mode control for attitude track...

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Chinese control Conference (CCC)

作者： Dapeng Yang Xiangdong Liu Zhongkui Li Yaohua Guo Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing Beijing CN

This paper considers the distributed attitude tracking problem of multiple spacecraft with disturbances and unknown inertia matrices. Based on the relative attitudes and angular velocities of neighboring spacecraft, we design a distributed robust controller to each follower to guarantee that the attitude errors between the followers and the leader converge to zero for any communication graph containing a directed spanning tree with the leader as the root. To deal with the problem of parameters uncertainties, we further propose a distributed adaptive sliding mode controller, under which the system is globally robust with respect to external disturbances and inertia matrices uncertainties.

关键词： Space vehicles Attitude control Robustness Vectors Angular velocity Synchronization Topology

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The algorithm of MIMU/odometer integrated navigation system aided by nonholonomic constraints

The algorithm of MIMU/odometer integrated navigation system ...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Shi Peng Xiao Xuan State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781479925667

The navigation precision drops rapidly when MIMU (Micro Inertial Measurement Unit) works alone. Odometer data are easy to get on land vehicle, but the performance of integration system of MIMU/odometer is not enhanced obviously. In this work, a novel method is designed using nonholonomic constraints. When vehicle travels without slide and jump, the velocity in the plane perpendicular to forward direction is zero, as well as acceleration. Taking velocity constraint and acceleration constraint as measurement value, new measurement models are established. Integrated navigation algorithm is designed with the help of Kalman filter. With this method, the position error is 150m after 600s, and heading attitude error is 0.1°, comparing the result that the position error expands to 300m after 150s only aided by odometer.

关键词： Vehicles Acceleration Global Positioning System Velocity measurement Noise Kalman filters

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Adaptive Wavelet Packet Filter-Bank Based Acoustic Feature for Speech Emotion Recognition

Adaptive Wavelet Packet Filter-Bank Based Acoustic Feature f...

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2013年中国智能自动化学术会议

作者： Yue Li Guobao Zhang Yongming Huang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

In this paper,a wavelet packet based adaptive filter-bank construction method is proposed,with additive Fisher ratio used as wavelet packet tree pruning criterion.A novel acoustic feature named discriminative band wavelet packet power coefficients(db-WPPC) is proposed and on this basis,a speech emotion recognition system is *** results show that the proposed feature improves emotion recognition performance over the conventional MFCC feature.

关键词： Speech emotion recognition Wavelet packets Filter-bank design Speech signal processing

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Multi-class classification via discriminative multiple subspace learning

Multi-class classification via discriminative multiple subsp...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Tang Tang Hong Qiao Suiwu Zheng State Key Laboratory of Management and Control for Complex Systems Organization Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479925667

Subspace learning has long been a fundamental yet important problem of modeling data distributions. In this paper, we propose to learn multiple linear subspaces in a supervised way for multi-class classification. To this end, a discriminative term redefining decision margin in terms of reconstruction error is incorporated into the model. The term enjoys similar properties of hinge loss function to the benefit of classification and leads to a training process seeking the balance between unsupervised learning and supervised learning. In the experiments on written digits dataset, our algorithm outperforms other methods proposed recently in both accuracy and computation efficiency.

关键词： Dictionaries Classification algorithms optimization Computational modeling Training Accuracy Principal component analysis

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Data-driven predictive control for networked control systems

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Information Sciences 2013年 235卷 45-54页

作者： Yuanqing Xia Wen Xie Bo Liu Xiaoyun Wang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper is concerned with the problem of data-driven predictive control for networked control systems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.

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Asymptotic backsteppinging stabilization of SISO nonlinear DAE subsystems using artificial neural networks

Asymptotic backsteppinging stabilization of SISO nonlinear D...

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2013 2nd International Conference on Manufacturing Engineering and Process, ICMEP 2013

作者： Qiang, Zang Ying, Zhou School of Information and Control Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China College of Automation Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9783037857076

The problem of robust stabilization for a class of SISO uncertain nonlinear Differential-Algebraic Eqyatuion subsystems is considered in this paper. The robust stabilization controller is proposed based on backstepping approach using two-layer Artificial Neural Networks (ANN) whose weights are updated on-line. A new adaptive algorithm is proposed to update the weights of ANN such that all signals in the closed-loop systems are bounded and the states are convergent asymptotically to the equilibrium through the proposed controller. © (2013) Trans Tech Publications, Switzerland.

关键词： Backstepping

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