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检索条件"机构=State Key Laboratory of Management and Control for Complex System"

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An Assist-as-Needed controller for Robotic Rehabilitation Therapy Based on RBF Network

An Assist-as-Needed Controller for Robotic Rehabilitation Th...

引用

2018 International Joint Conference on Neural Networks, IJCNN 2018

作者： Luo, Lincong Peng, Liang Wang, Chen Hou, Zengguang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781509060146

The rehabilitation training with active involvement and efforts of impaired subjects can enhance the outcome of rehabilitation therapies. To promote patients' voluntary engagement, a variety of assist as needed (AAN) controllers have been proposed for robot-aided therapy. However, patients' impairment level is not taken into account in the implementation of those control schemes. In this study, a novel AAN controller is developed for upper limb rehabilitation therapy. The control paradigm uses Gaussian radial basis function (RBF) network to learn the model of subjects' motor capability in workspace. The update of weight vectors of RBF network is based on a greedy strategy, which has the potential to promote subjects' voluntary engagement by providing task challenge for them. Considering the difference in the impairment degree of patients, the assistance and impedance level of robot control is regulated based on the task performance of patients. The results of experiments at four healthy subjects verify the feasibility and adaptability of the proposed AAN controller. © 2018 IEEE.

关键词： controllers

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The optimal control of discrete-time delay nonlinear system with dual heuristic dynamic programming

The optimal control of discrete-time delay nonlinear system ...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Wang, Bin Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642344749

In this paper, an effective iterative algorithm is proposed to deal with the optimal control problem of a class of nonlinear discrete-time delay systems. We define a meaningful performance index function to removing the disturbance of time delay terms. The iterative Dual Heuristic Programming (DHP) algorithm is introduced to design the optimal controller. Three neural networks are chosen to facilitate the implementation of the algorithm, which approximate the performance index function, the optimal control policy and the nonlinear delay system, respectively. A simulation example is given to demonstrate the validity of the proposed optimal control approach. For time-variant delay, this iterative algorithm shows the improved performance compared with other methods. © 2012 Springer-Verlag.

关键词： Neural networks

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Data-based characteristics analysis for linear discrete-time systems 19

Data-based characteristics analysis for linear discrete-time...

引用

19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Wang, Zhuo Liu, Derong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783902823625

In this paper, we develop data-based methods to analyze the characteristics of linear discrete-time systems, which have unknown parameter matrices. These characteristics include output controllability, asymptotic stability of the equilibrium point, bounded-input bounded-state stability, and bounded-input bounded-output stability. Our methods only use measured state and output data to verify the system properties. They are direct analysis methods and do not need to identify the unknown parameter matrices. These data-based methods not only can avoid identification errors, but also have lower computational complexity than traditional model-based analysis approaches. © IFAC.

关键词： Discrete time control systems

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A multi-target tracking approach combined with occlusion segmentation

A multi-target tracking approach combined with occlusion seg...

引用

4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Ding, Huan Zhang, Wensheng State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781612843735

Multiple-target tracking in complex scenes is one of the most complicated problems in computer vision. Handling the occlusion between objects is the key issue in multiple target tracking. This paper presents an occlusion segmentation-based method to track multiple people in complex situations which are captured by static monocular cameras. In the proposed method, we calculate the probabilistic histogram of each object's optical flow vector, then use this motion statistic information along with the color and appearance information to construct a new expression of pixel distance. Finally, a stepwise classification and K-means clustering method are taken advantages of to accomplish occlusion segmentation. Object tracking is handled by a particle filter-based tracking framework, and a probabilistic appearance model is used to find the best particle. Experiments are conducted using public challenging data set PETS 2009. Results show that our approach can improve the performance of the existing tracking approach and handle dynamic occlusions better. © 2011 IEEE.

关键词： Clutter (information theory)

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A convex-concave relaxation procedure based subgraph matching algorithm

A convex-concave relaxation procedure based subgraph matchin...

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4th Asian Conference on Machine Learning, ACML 2012

作者： Liu, Zhi-Yong Qiao, Hong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Based on the convex-concave relaxation procedure (CCRP), the (extended) path following algorithms were recently proposed to approximately solve the equal-sized graph matching problem, and exhibited a state-of-the-art performance (Zaslavskiy et al., 2009;Liu et al., 2012). However, they cannot be used for subgraph matching since either their convex or concave relaxation becomes no longer applicable. In this paper we extend the CCRP to tackle subgraph matching, by proposing a convex as well as a concave relaxation of the problem. Since in the context of CCRP, the convex relaxation can be viewed as an initialization of a concave programming, we introduce two other initializations for comparison. Meanwhile, the graduated assignment algorithm is also introduced in the experimental comparisons, which witness the validity of the proposed algorithm. © 2012 Z.-Y. Liu & H. Qiao.

关键词： Relaxation processes

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Deep nonlinear metric learning with independent subspace analysis for face verification

Deep nonlinear metric learning with independent subspace ana...

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20th ACM International Conference on Multimedia, MM 2012

作者： Cai, Xinyuan Wang, Chunheng Xiao, Baihua Chen, Xue Zhou, Ji State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781450310895

Face verification is the task of determining by analyzing face images, whether a person is who he/she claims to be. It is a very challenge problem, due to large variations in lighting, background, expression, hairstyle and occlusion. The crucial problem is to compute the similarity of two face vectors. Metric learning has provides a viable solution to this problem. Until now, many metric learning algorithms have been proposed, but they are usually limited to learning a linear transformation (i.e. finding a global Mahalanobis metric). In this brief, we propose a nonlinear metric learning method, which learns an explicit mapping from the original space to an optimal subspace, using deep Independent Subspace Analysis network. Compared to kernel methods, which can also learn nonlinear transformations, our method is a deep and local learning architecture, and therefore exhibits more powerful ability to learn the nature of highly variable dataset. We evaluate our method on the LFW benchmark, and results show very comparable performance to the state-of-art methods (achieving 92.28% accuracy), while maintaining simplicity and good generalization ability. © 2012 ACM.

关键词： Learning algorithms

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Graph-based background suppression for scene text detection

Graph-based background suppression for scene text detection

引用

10th IAPR International Workshop on Document Analysis systems, DAS 2012

作者： Shi, Cunzhao Xiao, Baihua Wang, Chunheng Zhang, Yang State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769546612

Detecting text in video or natural scene image is quite challenging due to the complex background, various fonts and illumination conditions. The preprocessing period, which suppresses the nontext areas so as to highlight the text areas, is the basis for further text detection. In this paper, a novel graph-based background suppression method for scene text detection is proposed. Considering each pixel as a node in the graph, our approach incorporates pixel-level and context-level features into a graph. Various factors contribute to the unary and pair wise cost function which is optimized via max-flow/min-cut algorithm [16] to get a binary image whose nontext pixels are suppressed so that text pixels are highlighted. Furthermore, the proposed background suppression method could be easily combined with other detection methods to improve the performance. Experimental results on ICDAR 2011 competition dataset show promising performance. © 2012 IEEE.

关键词： Edge detection

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A Target-Guided Neural Memory Model for Stance Detection in Twitter

A Target-Guided Neural Memory Model for Stance Detection in ...

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2018 International Joint Conference on Neural Networks, IJCNN 2018

作者： Wei, Penghui Mao, Wenji Zeng, And Daniel State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781509060146

Exploring user stances and attitudes is beneficial to a number of Web related research and applications, especially in social media platforms such as Twitter. Stance detection in Twitter aims at identifying the stance expressed in a tweet towards a given target (e.g., a government policy). A key challenge of this task is that a tweet may not explicitly express opinion about the target. To effectively detect user stances implied in tweets, target content information plays an important role. In previous studies, conventional feature-based methods often ignore target content. Although more recent neural network-based methods attempt to integrate target information using attention mechanism, the performance improvement is rather limited due to the underuse of this information. To address this issue, we propose an endto- end neural model, TGMN-CR, which makes better use of target content information. Specifically, our model first learns conditional tweet representation with respect to specific target. It then employs a target-guided iterative process to extract crucial stance-indicative clues via multiple interactions between target and tweet words. Experimental results on SemEval-2016 Task 6.A Twitter Stance Detection dataset show that our proposed method outperforms the state-of-the-art alternative methods, and substantially outperforms the comparative methods when a tweet does not explicitly express opinion about the given target. © 2018 IEEE.

关键词： Iterative methods

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Generalized Hamilton-Jacobi-Isaacs formulation-based neural network H ∞ control for constrained input nonlinear systems

Generalized Hamilton-Jacobi-Isaacs formulation-based neural ...

引用

19th International Conference on Neural Information Processing, ICONIP 2012

作者： Huang, Yuzhu Liu, Derong Wei, Qinglai State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642344749

In this paper, the nearly H∞ optimal control solution for discrete-time (DT) constrained input nonlinear systems is considered. First, to deal with the input constraints, a quasi-norm performance index function is introduced. Second, the corresponding constrained Hamilton-Jacobi-Isaacs (HJI) equation is formulated, and then the quasi L 2-gain analysis of the nonlinear system is employed. Third, an iterative algorithm based on the game theoretic interpretation of the generalized HJI (GHJI) equation by using neural networks (NNs) is presented. Moreover, the convergence of the algorithm to the optimal saddle point solution is proved, and the stability is also proved. Finally, a simulation example is given to illustrate the performance of the proposed method. © 2012 Springer-Verlag.

关键词： Nonlinear systems

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Simulation study of an FES-involved control strategy for lower limb rehabilitation robot

Simulation study of an FES-involved control strategy for low...

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5th International Conference on Intelligent Robotics and Applications, ICIRA 2012

作者： Chen, Yixiong Hu, Jin Zhang, Feng Hou, Zengguang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642335143

This paper proposes a functional electrical stimulation (FES)-involved control strategy for self-made exoskeleton lower limb rehabilitation robot for the training purpose of paraplegic patients caused by spinal cord injury (SCI) or stroke. Two muscles (Vastus Medialis and Riceps Femoris) are stimulated to produce active torque around knee joint which can be considered as a redundant actuator besides electrical motor. During the predefined trajectory tracking task, electrical motors compensate for the gravitational torque of the entire human-robot system, while the muscles provide torque calculated by a PD position/ velocity controller based on the tracking error. The FES-induced torque control is accomplished with combination of feedforward and feedback controller, former of which is obtained by applying off-line trained neural networks to map the relationship between desired active torque and FES parameters. Simulation results obtained by using Simulink toolboxes in Matlab verify the feasibility of this control strategy. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Torque control

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