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IEEE International Conference on Robotics and Biomimetics

作者： Yang Zhou Wei Wang Han Zhang Chen Wang Gang Xu Guangming Xie College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Department of Urban Studies and Planning Massachusetts Institute of Technology Cambridge MA USA 76315 Troop of the PLA Guangzhou China State Key Laboratory for turbulence and Complex Systems Peking University Beijing China Institute of Ocean Research Peking University Beijing China

ISBN: (纸本)9781728103785;9781728103778

Underwater wireless communication technology has been restricting the development of undersea resources for decades. We have proposed an effective underwater communication method (electrocommunication) for small underwater robots in our previous studies. In this article, we further study how electrode distance/spacing affects the communication range of electrocommunication between the robotic fish models. The working principle of electrocommunication is simplified by an electric dipole model. Based on the electric dipole model, the maximum theoretical distance of electrocommunication is derived as r=K 3 √(d 2 ) where d 2 is the distance between the receiving electrodes, and K is a constant related to the system and environmental parameters. Extensive experiments were conducted by varying the distance between the transmitting electrodes. The results show that the maximum experimental distance is basically consistent with the theoretical predictions, and that the communication distance is positively correlated with the electrode distance.

关键词： Electrodes Robots Receivers Transmitters Unmanned underwater vehicles Microcontrollers Underwater communication

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control theoretically explainable application of autoencoder methods to fault detection in nonlinear dynamic systems

arXiv

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arXiv 2022年

作者： Li, Linlin Ding, Steven X. Liang, Ketian Chen, Zhiwen Xue, Ting School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany Key Laboratory of Energy Saving Control and Safety Monitoring for Rail Transportation of Hunan Provincial School of Automation Central South University Changsha410083 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

This paper is dedicated to control theoretically explainable application of autoencoders to optimal fault detection in nonlinear dynamic systems. Autoencoder-based learning is a standard machine learning method and widely applied for fault (anomaly) detection and classification. In the context of representation learning, the so-called latent (hidden) variable plays an important role towards an optimal fault detection. In ideal case, the latent variable should be a minimal sufficient statistic. The existing autoencoder-based fault detection schemes are mainly application-oriented, and few efforts have been devoted to optimal autoencoder-based fault detection and explainable applications. The main objective of our work is to establish a framework for learning autoencoder-based optimal fault detection in nonlinear dynamic systems. To this aim, a process model form for dynamic systems is firstly introduced with the aid of control theory, which also leads to a clear system interpretation of the latent variable. The major efforts are made on the development of a control theoretic solution to the optimal fault detection problem, in which an analog concept to minimal sufficient statistic, the so-called lossless information compression, is introduced and proven for dynamic systems and fault detection specifications. In particular, the existence conditions for such a latent variable are derived, based on which a loss function and further a learning algorithm are developed. This learning algorithm enables optimally training of autoencoders to achieve an optimal fault detection in nonlinear dynamic systems. A case study on three-tank system is given at the end of this paper to illustrate the capability of the proposed autoencoder-based fault detection and to explain the essential role of the latent variable in the proposed fault detection system. Copyright © 2022, The Authors. All rights reserved.

关键词： Fault detection

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Reusable Energy-Absorbers Design Harnessing Snapping-Through Buckling of Multistable Metamaterials of Hierarchical Double-Curved Beam

SSRN

引用

SSRN 2023年

作者： Jin, Mingzhu Hou, Xiuhui Zhao, Wenhao Deng, Zichen School of Aeronautics Northwestern Polytechnical University Xi’an710072 China Institute of Extreme Mechanics Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi’an710072 China

We exploit the snapping-through buckling phenomenon exhibited by hierarchical DCB structures to devise a mechanical metamaterial with a unique deformation mode, encompassing multi-stability, multi-path, multi-platform, and multi-step characteristics, hence referred to as a 4M mechanical metamaterial. By employing DCB as fundamental building block elements, hierarchical metamaterials with two-dimensional series or parallel lattices are successfully constructed, as well as three-dimensional (3D) tubular geometries, denoted as DCB-n-m-C and DCB-n-m-M metamaterials, respectively. These metamaterials exhibit reversible energy absorption characteristics and the stiffness can be transformed from positive to negative under both small and large elastic deformations. Consequently, novel properties such as multistability, programmability, and reusable energy absorption characteristics are achieved. To comprehensively understand the mechanical response of the metamaterials, a thorough investigation into the influence of geometric parameters is conducted, including the number of polygonal edges, the number of the layers, the aspect ratio Q and material properties. This investigation involves a combination of theoretical analyses, numerical simulations, and experimental verifications. Notably, the force-displacement curves obtained during both loading and unloading process overlap almost completely, indicating the almost perfect recovery of the proposed structure after unloading. Furthermore, the effective crushing distance and energy absorption efficiency increase with the increase of geometric parameter Q. © 2023, The Authors. All rights reserved.

关键词： Energy absorption

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H∞ State Estimation for Time-Delayed Static Neural Networks Using an Improved Delay-Product-Type LKF

H∞ State Estimation for Time-Delayed Static Neural Networks...

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Chinese control Conference (CCC)

作者： Yong-He Lao Yu-Long Fan Liang-Tong Luo Chuan-Ke Zhang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan P. R. China

This paper is concerned with $H_{\infty}$ performance state estimation of static neural networks with a time-varying delay. First, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional (LKF) containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach.

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Haptic intelligent interfaces for NAO robot hand control

Haptic intelligent interfaces for NAO robot hand control

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International Conference on Advanced Mechatronic systems (ICAMechS)

作者： Octavian Melinte Luige Vladareanu Ligia Munteanu Hongnian Yu Shuang Cang Zeng-Guang Hou Gui-Bin Bian Hongbo Wang Dept. Robotics and Mechatronics Institute of Solid Mechanics of Romanian Academy Bucharest Romania Engineering and Computing Bournemouth University Dorset UK State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Parallel Robot and Mechatronic Sys. Lab. Yanshan University Qinhuangdao China

The paper presents a new approach on haptic interface control for NAO robotic hand. The haptic teleoperation of NAO robot hand raises some issues, mapping the haptic device dynamic being the most important. The mapping was achieved through Neural Network by determining a dynamic gain of robot haptic feedback. The results lead to the achievement of the haptic intelligent interfaces for the NAO robot hand control which can be integrated into an innovative haptic robot control system.

关键词： Decision support systems Humanoid robots Haptic interfaces Economic indicators Joints Mechatronics

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Correction to: Global finite-time set stabilization of spacecraft attitude with disturbances using second-order sliding mode control

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Nonlinear Dynamics 2022年第2期108卷 1847-1847页

作者： Guo, Zeyu Wang, Zuo Li, Shihua School of Automation Southeast University Nanjing People’s Republic of China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing People’s Republic of China

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Realizability of n-port resistive networks with 2n terminals

Realizability of n-port resistive networks with 2n terminals

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Asian control Conference

作者： Michael Z. Q. Chen Chanying Li Kai Wang Zhiqiang Zuo Minghui Yin Guanrong Chen Department of Mechanical Engineering University of Hong Kong Hong Kong China School of Automation Nanjing University of Science and Technology Nanjing China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin China Department of Electronic Engineering City University of Hong Kong Hong Kong China

In this paper, we consider the realizability problem of n-port resistive networks containing 2n terminals. A necessary and sufficient condition for any real symmetric matrix to be realizable as the admittance of an n-port resistive network containing 2n terminals is obtained. The condition is based on the existence of a parameter matrix. We then focus on a three-port resistive network containing six terminals. A necessary and sufficient condition is derived for any real symmetric matrix to be realizable as the admittance of a three-port resistive network containing six terminals and at most five positive elements, whose topological structure is properly restricted.

关键词： Symmetric matrices Ports (Computers) Admittance Educational institutions Resistors Joining processes Passive networks

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The Analysis of Muscle-Synergy Similarity between Walking and Pedaling Based on Variational Mode Decomposition and Non-Negative Matrix Factorization

The Analysis of Muscle-Synergy Similarity between Walking an...

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IEEE International Conference on engineering, Technology and Innovation

作者： Wangyang Ge Jinhua She Shijie Guo Feng Wang Juan Zhao Seiichi Kawata School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Engineering Research Center of the Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies Hebei Key Laboratory of Robot Sensing and Human-Robot Interaction Tianjin China School of Mechanical Engineering Hebei University of Technology Tianjin China

ISBN: (数字)9798350362435

ISBN: (纸本)9798350362442

Pedaling lower-limb rehabilitation robots are widely used in various stages of lower-limb rehabilitation because of their high safety and low requirements for patients' lower-limb strength. Researchers found that the activation sequence of the surface electromyographic (sEMG) signals of the muscles of the lower limb during pedaling is very similar to that of walking, which makes it possible to simulate the muscle force generation during walking by changing the pedal load during pedaling training. However, most pedaling lower-limb rehabilitation robots use constant loads, and it is of great importance to study the relationship between load and muscle synergy and to design load phase angle trajectories with higher muscle synergy consistency in the walking-pedaling motion to optimize the training effect of pedal-type rehabilitation robots. In this paper, we used variational mode decomposition (VMD) and nonnegative matrix factorization (NMF) to extract the muscle synergy features in each band of sEMG during walking and pedaling and to study the similarity of pedaling and walking and the influence of pedal load on muscle synergy consistency.

关键词： Legged locomotion Training Technological innovation Time series analysis Muscles Assistive robots Feature extraction Trajectory Safety Matrix decomposition

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A New Approach for Face Anti-Spoofing Using Handcrafted and Deep Network Features

A New Approach for Face Anti-Spoofing Using Handcrafted and ...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Polash Kumar Das Bin Hu Chang Liu Kaixin Cui Prabhat Ranjan Gang Xiong School of Electronic and Information Engineering South China University of Technology Guangzhou China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China College of Computer Science Sichuan University Chengdu China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Cloud Computing Center Chinese Academy of Science Dongguan China

In biometrics, face recognition methods are achieving momentum with recent progress in the computer vision(CV). Face recognition is widely used in the identification of an individual's identity. Unfortunately, in recent research work has revealed this face biometrics system is unprotected to spoofing attacks using by very low price instrument such as printed 2D photos attack, 3D masking attack and taking videos using smart devices (reply attack). Therefore, a Liveness Attack Detection (LAD) approach is needed to improve the high-quality security of face recognition system. Most of the earlier worked LAD methods for face anti-spoofing methods have highlight on using the handcrafted features, which are developed by expert knowledge of researcher. As example Gabor filter, Histogram of Oriented Gradients, local ternary pattern, and the Local Binary Pattern. Because of that, the extracted features consider limited factors of the problem, yielding a capture accuracy that is very low and changes with the point of presentation in attack face images. The deep learning method has developed in the computer vision research community, which is proven to be suitable for automatically training. In this article, we approach to mix or combine the handcrafted features and deep neural network features to design the discriminant face spoofing detection. The handcrafted features were based on LBP analysis. We examine the features information from the brightness and the chrominance channels using LBP descriptor. In deep features, we present an approach based on pre-trained convolutional neural network VGG-16 model using static features to recognize video and printed(2D) photo attacks. By attaching this two types of image features on our dataset and public databases, we get good results to identify real and attack images feature, called hybrid features, which has better discrimination ability to understand spoofing image feature.

关键词： Face Videos Feature extraction Databases Face recognition Password

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The Multi-Blockchain Based Data Trading Markets with Novel Pricing Mechanisms

SSRN

引用

SSRN 2022年

作者： Li, Juanjuan Li, Junqing Wang, Xiao Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Qingdao Academy of Intelligent Industries Qingdao266109 China School of Mathematics Renmin University of China Beijing100872 China Macao Institute of Systems Engineering Macau University of Science and Technology Macau 999078 China

Aiming to deal with the challenge of data security and data pricing in data trading markets, we propose the novel multi-blockchain-based framework and design the related pricing mechanisms. Specifically, data recording and trading are conducted separately in the Data Blockchain (DChain) and the Value Blockchain (VChain). Based on these blockchains, two-layer data trading markets are established to manage the initial data trading in the primary market and the data resale in the secondary market. Pricing mechanisms are proposed to protect the formulated data trading markets against strategic trading behaviors and balance the payoffs of both suppliers and users. In the regular data trading on VChain-S2D, two auction models are used to deal with users' strategic bidding in terms of the demand scale, where the incentive-compatible Vickrey-Clarke-Groves (VCG) model is dedicated to the low-demand trading scenario, while the nearly incentive-compatible Monopolistic Price (MP) model is for the high-demand trading scenario. In the temporary data trading on VChain-D2S, a reverse auction mechanism named Two-Stage Obscure Selection (TSOS) is designed to regulate both suppliers' quoting and users' valuation strategies. Moreover, experiments are carried out to validate our theoretical analysis. Our work is expected to enhance the data security and improve the trading efficiency. © 2022, The Authors. All rights reserved.

关键词： Blockchain

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