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American control Conference

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China the School of Electrical and Information Engineering Tianjin University Tianjin 300072 China the School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781509045839

In this paper, the adaptive critic method is applied to solve a class of continuous-time event-based H_∞ control problems. The present control problem is transformed into a two-player zero-sum differential game and the adaptive critic structure is employed for coping with the event-based minimax optimization. Next, the event-based optimal feedback control and the time-based worst-case disturbance law are learned by training a critic neural network. In addition, the closed-loop system is constructed with stability analysis of the critic error dynamics and the sampled-data plant. The exclusion of the infamous Zeno behavior of the present event-based control design is also discussed. Finally, the control performance of the present approach is evaluated through simulation study.

关键词： exclusion infamous Zeno exclusion critic Event-based Data sampling control performance design control

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External consensus of networked multi-agent systems with nonlinear dynamics and random network delay

External consensus of networked multi-agent systems with non...

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Asian control Conference

作者： Qi Lei Jia-Hui Li Guo-Ping Liu Min Wu School of Information Science and Engineering University of Central South University Changsha China School of Engineering University of South Wales Pontypridd U.K. School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781509015740;9781509015733

In this paper, the external consensus problem of networked multi-agent systems with fixed undirected topology, random network delay and nonlinear dynamics is considered. The unknown nonlinear dynamics existing in the systems can be described as RBF-ARX model. Besides, the random network delay can be compensated by introducing the prediction strategy. The RBF-ARX model is used as prediction model to design the output predictor, which is to generate the prediction sequence of control input and agent's output. Then, the designed selector chooses the proper value from the available sequences corresponding to the value of the network delay. Based on the mentioned above, a distributed external consensus control algorithm is proposed to make the considered systems with external reference input achieve consensus. Finally, an example is given to illustrate the validity of the proposed algorithm.

关键词： Delays Nonlinear dynamical systems Algorithm design and analysis Prediction algorithms Predictive models Network topology Radial basis function networks

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12.2: A 3D Display Parallel System: Light Field Re-rendering and Depth Sense Optimization

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SID Symposium Digest of Technical Papers 2018年第S1期49卷

作者： Renjing Pei Kui Ma Feiyue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences East Zhongguanchun Road No. 95 Haidian District Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing Parallel Optics Technology Innovation Center Qingdao Academy of Intelligent Industries Qingdao

The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye's visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer's demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance.

关键词： 3D Display Parallel System Depth Sense Light Field Re-rendering 3D Video Processing One-shot Segmentation

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Pole placement for discrete-time systems via multiple parametric Lyapunov equations

Pole placement for discrete-time systems via multiple parame...

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International Workshop on Variable Structure systems, VSS

作者： Qingling Wang Yuanda Wang School of Automation Southeast University Nanjing China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

This paper investigates the pole placement problem of discrete-time systems. To retain the advantages of the parametric discrete-time Lyapunov equation, matrix-partitioning idea is used to derive a new pole shift lemma. Starting from system matrix transformations, a recursive method that shifts every eigenvalue of a discrete-time system separately without mode decomposition in each step is proposed. Compared with existing methods, this one not only leads to analytical solutions to feedback gains but also may need low computation cost on flexible pole placement. As an application, the semiglobal stabilization with guaranteed flexible pole placement for saturated discrete-time systems is achieved using this method.

关键词： Linear systems Symmetric matrices Eigenvalues and eigenfunctions Design methodology Discrete-time systems control systems complex systems

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A robust traffic driver face detection method

A robust traffic driver face detection method

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Dechao Luo Xiaobo Lu Changhui Hu Xiang Peng Wei Wang 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)9781509034857

Face detection technology is a hot topic in the past recent years. It has been maturely applied to many practical areas. However, the driver face detection is still an open problem to solve. In this paper, we proposed an improved method to promote the face detection rate and apply it to the images from the monitoring videos. The first step is to detect the car from the images according to an off-line learning method. Then the method based on additional off-line learning method is the front level for skin color feature in order to correctly detect the driver face. The proposed systems are implemented on the various complicated road environment. The results show that the proposed method improves the efficiency of the driver face detection and is of strong robustness on having glasses, driver head rotation, and lighting change.

关键词： Skin Color Face detection Feature extraction Automobiles Face

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A two-column convolutional neural network for facial point detection

A two-column convolutional neural network for facial point d...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Wei Wang Xiaobo Lu Jiaji Song Cong Chen 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)9781509034857

This paper proposes a two-column convolutional neural network algorithm for face point detection, which proves better performance than single-column. Because of the deep level structure, global texture features are extracted at higher layers of the network, and the results of keypoint location remains high accuracy. In the first column, we take the R, G, B channel component of original image as input to train the neural network respectively and calculate the average location results. In the second one, we use Sobel operator to extract first-order derivative feature of original image and regard it as the input to train another convolutional network. The location results of two columns above are fused with appropriate proportion to ensure better results. Experimental result on LEW dataset shows the performance of the proposed parallel structure better than single convolutional network, and it stays robust due to occlusions, large pose variations and extreme lighting.

关键词： Neural networks

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Human physical activity recognition based on computer vision with deep learning model

Human physical activity recognition based on computer vision...

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IEEE Instrumentation and measurement Technology Conference

作者： Lingfei Mo Fan Li Yanjia Zhu Anjie Huang School of Instrument Science and Engineering Southeast University Nanjing China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

ISBN: (纸本)9781467392211

Human activity recognition is an active research area in the computer science because it is widely used in the fields of the security monitoring, health assessment, human machine interaction and other human related content searching. In this paper, a computer vision model based on the deep learning algorithm is proposed, which can recognize the human physical activity based on the skeleton data of the human body from the sensor of Microsoft Kinect. This model uses the human skeletons data from the CAD-60 dataset to recognize the human physical activity without using any prior knowledge. It can reduce the works on the stage of data preprocessing and feature extraction. It can also improve the generalization performance and robustness of the model, and give a better understanding of the human physical activity. Different tricks which can improve the performance of the neural networks, such as some regularization methods and other activation functions are tested. Finally, a convolutional neural network is used for the feature extraction, and a multilayer perceptron is used as the following classifier. The model can recognize twelve types of activities and the accuracy rate is 81.8%. It demonstrates that it is very effective to use the convolutional neural network to supervised learning and this model applies to human physical activity recognition.

关键词： Feature extraction Training Skeleton Neurons Computational modeling Biological neural networks Machine learning

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Environment-Dependent Payoffs in Finite Populations

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Chinese Physics Letters 2015年第2期32卷 160-162页

作者：徐微鸿张艳玲谢广明封雪 Center for Systems and Control State Key Laboratory for Turbulence and Complex SystemsCollege of EngineeringPeking University

In finite population games with weak selection and large population size, when the payoff matrix is constant, the one-third law serves as the condition of a strategy to be advantageous. We generalize the result to the cases of environment-dependent payoff matrices which exhibit the feedback from the environment to the population. Finally, a more general law about cooperation-dominance is obtained.

关键词： Environment-Dependent Payoffs in Finite Populations

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Optimal Innovation-Based Deception Attack on Remote State Estimation

Optimal Innovation-Based Deception Attack on Remote State Es...

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American control Conference

作者： Shuang Wu Ziyang Guo Dawei Shi Karl Henrik Johansson Ling Shi Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology 100081 China ACCESS Linnaeus Centre School of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781509045839

The security issue in cyber-physical systems has attracted growing interests in the last decades. This paper considers how false data injection attack can degrade the estimation quality of a remote state estimation system. In this system, smart sensors measure a dynamic process and send preprocessed data through a communication network to a remote estimator to estimate the process. It is assumed that there are malicious attackers in the communication network, who are able to obtain and falsify all the data sent by the sensors. It is common that the remote estimator is equipped with a residue-based detector to detect potential attacks. We propose a class of deception attack and analyze its feasibility. We show that the proposed attack enables the attacker to inject false data into the remote estimator without being detected. We derive a criterion to judge the optimality of performance of this type of attack in the sense of maximizing the estimation error covariance. Furthermore, we find that a simple linear attack strategy, which flips the sign of intercepted signal, satisfies the optimality criterion. We present numerical examples to illustrate our theoretical results.

关键词： Cyber-physical systems (CPS) deception attack remote state estimation

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7.3: Compare Variation of User's EEG Owing to Parallax Cue

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SID Symposium Digest of Technical Papers 2018年第S1期49卷

作者： Haichen Hu Danli Wang Kang Yue Xinpan Yang Steve C. Chiu Beijing Key Lab of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China College of Science and Engineering Idaho State University Pocatello America

3D display has become increasingly popular in many fields. It can provide incredible immersion compared with 2D display. There are many researches referring to the change of user about no matter subjective experience or objective physiology signal while watching 3D content. Similarly, in this paper, we study the variation of user’s EEG when the user watched 3D content. However, we only focus on parallax cue and avoid other cues of 3D content by using Random Dot Stereogram(RDS) as visual stimulus. We designed an experiment which asked the subject to watch RDS with nine kinds of parallaxes(0,±0.5,±1.1,±1.3,±1.7). The users watched one RDS for 1 minute and then closed eyes and rest for 1 minute every time. During watching, EEG signal with 30-channel was recorded. The result suggests that significant variation of the user’s EEG data occurred in the Alpha (8–13Hz) and Beta(14–30Hz) frequency band by different parallax’s comparison. And we found not only parallax but also electrode position can impact the user’s EEG data significantly. Accurately, the EEG data has a significant change in six electrodes position in both frequency bands including CZ, PZ, OZ, O2 in international 10–20 system. It means those electrode positions we detect can be regarded as typical positions where we record EEG signal. It will simplify the process of EEG signal acquisition when we need to study the relationship between parallax cue of 3D display and the user further.

关键词： EEG Parallax RDS 3D

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