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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Chen, Yixiong Hu, Jin Kasabov, Nikola Hou, Zengguang Cheng, Long State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

ISBN: (纸本)9783642420504

One of the most important issues among active rehabilitation technique is how to extract the voluntary intention of patient through bio-signals, especially EEG signal. This pilot study investigates the feasibility of utilizing a 3D spiking neural networks-based architecture named NeuCube for EEG data classification in the rehabilitation practice. In this paper, the architecture of the NeuCube is designed and a Functional Electrical Stimulation (FES) rehabilitation scenario is introduced which requires accurate classification of EEG signal to achieve active FES control. Three classes of EEG signals corresponding to three imaginary wrist motions are collected and classified. The NeuCube architecture provides promising classification results, which demonstrates our proposed method is capable of extracting the voluntary intention in the rehabilitation practice. © Springer-Verlag 2013.

关键词： Neural networks

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Adaptive Dynamic Programming for Solving Non-Zero-Sum Differential Games

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IFAC Proceedings Volumes 2013年第20期46卷 586-591页

作者： Hongliang Li Derong Liu Ding Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

In this paper, a novel adaptive dynamic programming algorithm based on policy iteration is developed to solve online multi-player non-zero-sum differential game for continuous-time nonlinear systems. This algorithm is mathematically equivalent to the quasi-Newton's iteration in a Banach space. The implementation using neural networks is given, where a critic neural network is used to learn its value function, and an action neural network sharing the same parameters with the corresponding critic neural network is used to learn its optimal control policy for each player. All the critic and action neural networks are updated online in real-time and continuously. A simulation example is presented to demonstrate the effectiveness of the developed scheme.

关键词： Adaptive Dynamic Programming Learning control Adaptive control Neural Networks Differential Games Stability

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Neuro-Optimal control of Unknown Nonaffine Nonlinear systems with Saturating Actuators

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IFAC Proceedings Volumes 2013年第20期46卷 574-579页

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

This paper develops an adaptive optimal control for the infinite-horizon cost of unknown nonaffine nonlinear continuous-time systems with control constraints. A recurrent neural network (NN) is constructed to identify the unknown system dynamics with stability proof. Then, two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal value, respectively. By using this architecture, the action NN and the critic NN are tuned simultaneously, without the requirement of the knowledge of system dynamics. In addition, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded based on Lyapunov's direct method. A simulation example is provided to verify the effectiveness of the developed theoretical results.

关键词： Actuator saturation Adaptive control Neural networks Nonaffine systems Optimal control Unknown nonlinear systems

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Direct adaptive output feedback control for MIMO uncertain nonlinear discrete-time systems based on neural networks

Direct adaptive output feedback control for MIMO uncertain n...

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Chinese control Conference (CCC)

作者： Xiong Yang Derong Liu Ding Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

This paper develops a novel neural-network-based direct adaptive control scheme for a class of multi-input-multi-output uncertain nonlinear discrete-time (DT) systems in the presence of unknown bounded disturbances. By employing feedback linearization methods, neural network (NN) approximation can cancel the nonlinearity of the DT systems. Meanwhile, the weights of NNs are directly updated online instead of preliminary offline training. In addition, unlike most literatures, the condition for persistent excitation is removed. Based on Lyapunov's direct method, both tracking errors and weight estimates are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. Finally, an example is provided to demonstrate the effectiveness of the proposed approach.

关键词： Artificial neural networks Nonlinear systems Vectors Adaptive control Trajectory MIMO

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Neuro-control to energy minimization for a class of chaotic systems based on ADP algorithm

Neuro-control to energy minimization for a class of chaotic ...

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Song, Ruizhuo Xiao, Wendong Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642420566

This paper discusses the energy minimization problem of a class of chaotic systems, and constructs an optimal neuro-controller based on adaptive dynamic programming (ADP) algorithm. To learn the optimal performance index and control policy, an iterative algorithm is established. To prove the convergence of the presented iterative algorithm, theorems with rigorous and detailed proofs are given. It is proven that the iterative performance index functions are monotone decreasing and converge to the minimum energy. A simulation example is used to indicate that the presented energy minimization control method is effective. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Chaotic systems

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Underwater target search with robotic fish based on an improved Camshift algorithm

Underwater target search with robotic fish based on an impro...

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Chinese Automation Congress (CAC)

作者： Shifeng Chen Junzhi Yu Feihu Sun Min Tan State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

Biomimetic robotic fish has the distinct advantage of efficient propulsion and high maneuverability over conventional underwater vehicles. This paper addresses the underwater target search issue in a free-swimming robotic fish with embedded vision. In particular, we use the stored original image to acquire the color characteristics of the target and propose an improved Camshift algorithm based on the light intensity distribution to search the target in the captured image. Then the robotic fish is driven towards the identified target smoothly with the aid of bio-inspired Central Pattern Generator (CPG) control. All tracking algorithms are implemented in real time with a hybrid control system combining an embedded microprocessor (TI DM3730) and a microcontroller (ATmega128). Latest aquatic experiments demonstrate that a fairly good tracking effect is resulted and the interference caused by the mirror image effect is largely eliminated. The proposed technical scheme offers an alternative to target search in relatively complex underwater environments.

关键词： Marine animals Mirrors Robot kinematics Target tracking Image color analysis Microprocessors

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What is the uniqueness of growth pattern in human flesh search organization?

What is the uniqueness of growth pattern in human flesh sear...

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Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2013

作者： Wang, Tao Zhang, Qingpeng Fu, Julei Wang, Xiao Zheng, Suncong College of Information System and Management National University of Defense Technology Changsha 410073 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Systems and Industrial Engineering University of Arizona Tucson AZ United States

ISBN: (纸本)9783642396922

Human Flesh Search is an explosive Web phenomenon these years in China, especially when new media, such as Weibo, appeared. In this research, we present the empirical studies about growing patterns of participated Human Flesh Search user, and unveiled one unique growing property. Based on the empirical findings, we compare it with two others results, one is the common Weibo's growth pattern, and the other is the popularity growth pattern of photo in Flickr. Some differences are proposed and analyzed briefly. © 2013 Springer-Verlag.

关键词： Social networking (online)

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An enhanced dual-finger robotic Hand for Catheter manipulating in vascular intervention: A preliminary study

An enhanced dual-finger robotic Hand for Catheter manipulati...

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International Conference on Information and Automation (ICIA)

作者： Gui-Bin Bian Xiao-Liang Xie Zhen-Qiu Feng Zeng-Guang Hou Peng Wei Long Cheng Min Tan The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

Cardiovascular disease is a class of diseases that involve the heart and blood vessels, which is the leading cause of deaths globally. Vascular interventional surgery is an effective treatment. As belongs to minimally invasive surgery (MIS), it is more popular due to the advantages of smaller injury, faster recovery and higher accuracy rate. However, it needs up to 10 years to train a skilled surgeon for minimally invasive cardiovascular surgeries. The surgeon cannot avoid receiving the excessive dose of X-ray due to long time operation in daily work. A dual-finger robotic hand (DRH) was introduced to assist the surgeon in manipulating the catheter/guide wire. As a surgical device, DRH is aiming at simple mechanism, ease to use and convenient sterilization. It was carefully investigated how the surgeon manipulates the catheter/guide wire. The bionic thumb and forefinger were designed to imitate human's. Compared to human's, the two bionic fingers are enhanced due to that they can advance the catheter/guide wire without moving the whole hand. The DRH mechanism was carefully designed. A console was also designed for the surgeon to manipulate DRH. After the DRH control was done, the minimum robotic cardiovascular interventional system was formed. Experimental results have validated the feasibility of DRH and the robotic system. Future work regarding DRH is also discussed.

关键词： Catheters Rubber Connectors Surgery Robots Couplers Transducers

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Action Knowledge Extraction from Web Text

Action Knowledge Extraction from Web Text

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IEEE International Conference on Intelligence and Security Informatics

作者： Ansheng Ge Wenji Mao Daniel Zeng Lei Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467362146

Action knowledge is an important type of behavioral knowledge and of vital importance to many applications in social computing, especially in behavior modeling, analysis and prediction. In this paper, we present a computational method to action knowledge extraction from online media. Our approach is based on mutual bootstrapping and combined with knowledge reasoning. Compared with the related work, our approach can acquire more types of action knowledge, and needs much less human labor. We evaluate the performance of our method using the Web textual data from security informatics domain. The experimental results show the effectiveness of our proposed method.

关键词： Action knowledge Knowledge extraction Bootstrapping Reasoning

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Robust mean-shift tracker with local saliency feature and spatial pattern preserved metric

Robust mean-shift tracker with local saliency feature and sp...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Linshan Liu Suiwu Zheng Hong Qiao Min Wang State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479925667

Robust object tracking in crowded and cluttered dynamic scenes is a very difficult task in robotic vision due to complex and changeable environment and similar features between the background and foreground. In this paper, we present an improved mean-shift tracker which uses discriminative local saliency feature and a new spatial pattern preserved similarity metric method to overcome above difficulties in mean-shift based tracking approaches. The local saliency feature, which is composed of contrast color, texture and gradient around the target, is proposed to find the most distinguished features between the target and background, and it could enhance the tracking performance greatly in the cluttered and complex environment. Another important benefit of this feature is that the saliency map form could be easily embedded into the mean-shift framework. The new similarity metric try to preserve the spatial pattern to reduce the similarity errors caused by different spatial structure. It is beneficial to the mean-shift tracker to face the targets and scenes which has identical texture and color feature and with different spatial patterns. Finally, the efficiency of the proposed improved mean-shift tracker is validated through the plenty experimental results and analysis.

关键词： Target tracking Histograms Image color analysis Robustness Kernel Color

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