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International Conference on Communication Technology (ICCT)

作者： Tierui Gong Zhifeng Liu Zhijia Yang Gengshan Wang Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

To address the performance degradation of wide-band spectrum sensing by sub-Nyquist sampling (SNS) in wireless fading channels, two compressive subspace learning (CSL) algorithms are proposed for signal subspace learning based on antenna cross-correlations for further improving the sensing performance. Both algorithms are developed based on different organizations of SNS samples, and both exploit space diversity and noise uncorrelations between antennas. We further establish the expressions for statistical covariance matrices (SCMs) obtained by SNS samples in the multi-antenna SNS cognitive radio system. Based on the derived SCM expressions, conditions to ensure SCMs without noise contamination are given. Simulations validate the derived conditions and show the improvement on sensing performance over related works.

关键词： Wideband Robot sensing systems Broadband antennas Fading channels Spatial diversity

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An Improved Upper Bound on the Maximum Eigenvalue of Exponential Model Based Spatial Correlation Matrices in Massive MIMO systems

An Improved Upper Bound on the Maximum Eigenvalue of Exponen...

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International Conference on Communication Technology (ICCT)

作者： Tierui Gong Guang Yang Ke Mu Chun Zhao Zhijia Yang Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

Massive Multiple-Input, Multiple-Output (MIMO) communications are considered as one of the most promising directions for the next generation communications and have attracted extensive research interests. The using of exponential model is recognized as an effective manner to describe the spatial correlation matrix in a spatially correlated MIMO channel for its simple form and accurate fitting on the experimental measurements. Based on this useful exponential model, an improved upper bound on the maximum eigenvalue of the spatial correlation matrix is given in this paper. Complying with the existing results, the proposed upper bound is also a function of the number of antennas and the absolute value of correlation coefficient. However, the proposed upper bound is obtained using a trace-based derivation, which is tighter than existing results in high spatial correlation massive MIMO systems. Simulations show that the proposed upper bound is closer to the true maximum eigenvalues for both uniform linear array and uniform planar array scenarios, which is expected to be widely used in massive MIMO systems.

关键词： Correlation Eigenvalues and eigenfunctions Upper bound Transmission line matrix methods MIMO communication Antenna arrays

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Research on Collaboration Method of Edge IoT Agent Based on Actor Model

Research on Collaboration Method of Edge IoT Agent Based on ...

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Power and Energy Engineering (ICPEE), International Conference on

作者： Bowen Zhang Weiwei Miao Lei Wei Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Information & Telecommunication Branch State Grid Jiangsu Electric Power Co. Ltd. Nanjing China State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (纸本)9781665420471

Focusing on the resource constrained IoT agent collaboration requirements at the edge of the power Internet of things, this paper proposes an edge agent collaborative computation method based on Actor model to satisfy the rapid processing and response requirements of large-scale data in the perception layer of the power Internet of things. Through a unified programming model, this paper can divide the collection and analysis of sensing data in the sensing layer of the power Internet of things into functional components, which can be deployed in different edge IoT agents, to improve the rapid processing ability of edge-side data. At the same time, the components achieve the function cooperation through the message passing mechanism. Finally, this paper implements the proposed scheme based on Akka framework, and designs the edge IoT agent collaborative computing prototype. The prototype system experiments show that the proposed scheme can split the complex services with high resource requirements into different components and deploy them in different edge IoT agents. The proposed method can improve the resource utilization and data processing capacity of the edge IoT agent of the power Internet of things, while ensuring the real-time requirements of edge service analysis.

关键词： Computational modeling Message passing Collaboration Prototypes Programming Data models Real-time systems

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Identification of muscle morphology with noncontact capacitive sensing: Preliminary study

Identification of muscle morphology with noncontact capaciti...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Enhao Zheng Jiacheng Wan Dongfang Xu Qining Wang Hong Qiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Information Engineering China university of geosciences (Beijing) Beijing China The Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Human-machine interface with muscle signals serves as an important role in the field of wearable robotics. To compensate for the limitations of the existing surface Electromyography (sEMG) based technologies, we previously proposed a noncontact capacitive sensing approach that could record the limb shape changes. The sensing approach frees the human skin from contacting to the metal electrodes, thus enabling the measurement of muscle signals by dressing the sensing front-ends outside of the clothes. We validated the capacitive sensing in human motion intent recognition tasks with the wearable robots and produced comparable results to existing studies. However, the biological significance of the capacitance signals is still unrevealed, which is an indispensable issue for robot intuitive control. In this study, we address the problems of identifying the relationships between the muscle morphological parameters and the capacitance signals. We constructed a measurement system that recorded the noncontact capacitive sensing signals and the muscle ultrasound (US) images simultaneously. With the designed device, five subjects were employed and the US images from the gastrocnemius muscle (GM) and the tibialis anterior (TA) muscle during level walking were sampled. We fitted the calculated muscle morphological parameters (the pinnation angles and the muscle fascicle length) and the capacitance signals of the same gait phases. The results demonstrated that at least one-channel capacitance signal strongly correlated to the muscle morphological parameters (R 2 > 0.5, quadratic regression). The average R 2 s of the most correlated channels were up to 0.86 for pinnation angles and 0.83 for the muscle fascicle length changes. The interesting findings in this preliminary study suggest the biological physical significance of the capacitance signals during human locomotion. Future efforts are worth being paid in this new research direction for more promising results.

关键词： Muscles Robot sensing systems Capacitance Legged locomotion Electrodes Ultrasonic variables measurement

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A Piecewise-Markovian Lyapunov Approach to Reliable Output Feedback control for Fuzzy-Affine systems With Time-Delays and Actuator Faults

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2723-2735页

作者： Wei, Yanling Qiu, Jianbin Shi, Peng Wu, Ligang State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

This paper addresses the problem of delay-dependent robust and reliable H-infinity static output feedback (SOF) control for a class of uncertain discrete-time Takagi-Sugeno fuzzy-affine (FA) systems with time-varying delay and actuator faults in a singular system framework. The Markov chain is employed to describe the actuator faults behaviors. In particular, by utilizing a system augmentation approach, the conventional closed-loop system is converted into a singular FA system. By constructing a piecewise-Markovian Lyapunov-Krasovskii functional, a new H-infinity performance analysis criterion is then presented, where a novel summation inequality and S-procedure are succeedingly employed. Subsequently, thanks to the special structure of the singular system formulation, the piecewise-affine SOF controller design is proposed via a convex program. Lastly, illustrative examples are given to show the efficacy and less conservatism of the presented approach.

关键词： Piecewise Markovian Lyapunov functional reliable output feedback control time-varying delay T-S fuzzy-affine (FA) systems

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Adaptive tracking control of flapping wing micro-air vehicles with averaging theory

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CAAI Transactions on Intelligence Technology 2018年第1期3卷 18-27页

作者： Chen Qian Yongchun Fang Institute of Robotics and Automatic Information Systems College of Computer and Control Engineering Tianjin 300353People's Republic of China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin 300353 People's Republic of China

An input constrained adaptive tracking controller is designed for flapping micro aerial vehicles, wherein the moving averaging filter is adopted to estimate the averaged states of the system. Specifically, in the outer loop controller, an observer is constructed to estimate the disturbances within the system. Moreover, the constrained thrust is designed to keep the frequency in a proper region so as to meet the requirement of average estimation. Then, a tracking differentiator is used to provide trackable trajectories for the inner loop. Subsequently, a new quaternion- based hybrid attitude tracking controller is designed which successfully deals with high-frequency noises and avoids possible chattering. As supported by mathematical analysis, the proposed control strategy guarantees the uniform ultimate boundedness of the closed-loop system, and it keeps the control torques within the permitted range to meet the application requirement. At last, numerical simulations are carried out to support the validity of the proposed controller, whose results are satisfactory even when the thrust and torques are saturated.

关键词：飞行器跟踪器人工智能发展现状

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Communication Scheme of Cloud Platform for the Lower Limb Exoskeleton Rehabilitation Robot

Communication Scheme of Cloud Platform for the Lower Limb Ex...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Ye Yuan Guang-Zhong Cao Aibin Zhu Xing Lyu Yulong Wang Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen University Shenzhen China Shaanxi Key Laboratory of Intelligent Robots Institute of Robotics & Intelligent Systems Xi'an Jiaotong University Xi'an China Shenzhen Second People's Hospital Rehabilitation Center The First Affiliated Hospital of Shenzhen University Shenzhen China

The following topics are dealt with: mobile robots; learning (artificial intelligence); robot vision; motion control; medical robotics; position control; control engineering computing; human-robot interaction; feature... 详细信息

ISBN: (数字)9781728157153

ISBN: (纸本)9781728157160

关键词： Robot sensing systems Cloud computing Protocols Exoskeletons Robot kinematics Logic gates

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Fault Detection using Common and Specific Variable Decomposition for Nonlinear Multimode Process

Fault Detection using Common and Specific Variable Decomposi...

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Chinese Automation Congress (CAC)

作者： Shuai Li Xiaofeng Zhou Haibo Shi Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Due to the change of operating conditions including external environments and production schemes, there are usually multiple modes in most industrial processes. Moreover, different linear and nonlinear correlations simultaneously coexist in different modes, which brings difficulty to fault detection. Aiming at this problem, the paper proposes a fault detection method using common and specific variable decomposition for nonlinear multimode process. The proposed method takes into account the linear and nonlinear correlations in different modes and utilizes the common and specific modeling ideas for enhancing the performance of fault detection in multimode process. First, the multimode process data are divided into the common variable subspace and the specific variable subspace based on sliding window low-order and high-order statistics. Then, the nonlinearity coefficient is used to evaluate the linear and nonlinear correlations for each variable subspace. Subsequently, the common and specific PCA-KPCA-SPCA-based multimode process modeling is developed for fault detection. The fault detection results of the Tennessee Eastman (TE) process demonstrate the feasibility and effectiveness of the proposed method.

关键词： Fault detection Correlation Principal component analysis Silicon Process control Manufacturing Loading

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EEG-Based Odor Recognition Using Channel-Frequency Convolutional Neural Network

EEG-Based Odor Recognition Using Channel-Frequency Convoluti...

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第三十八届中国控制会议

作者： Xiaonei Zhang Huirang Hou Qinghao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

Analyzing the response of the human brain to odors is critical to assess the function of olfactory and cognition. In this paper, an EEG(electroencephalograph)-based odor perception dataset is collected from ten subjects using thirteen odors stimuli. Based on the developed dataset, we employ channel-frequency convolutional neural network(CFCNN), combined with differential entropy(DE) features from different channels and frequency bands, to classify five odors that were consistently considered pleasant by the ten subjects. Meanwhile, the k-nearest neighbor(k-NN), linear discriminant analysis(LDA), support vector machine(SVM) and back propagation neural network(BPNN) are used as competing methods. The experimental results show that CFCNN is superior to the classic baselines and yields the highest accuracy in distinguishing five pleasant odors. Furthermore, compared with other four frequency bands, the gamma band presents the best classification accuracy, proving the closed relation between the olfaction and gamma band activity of the brain.

关键词： EEG olfaction classification CFCNN differential entropy

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Autonomous docking and energy sharing between two types of robotic agents

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IFAC-PapersOnLine 2018年第29期51卷 406-411页

作者： Babi, Anja Mandi, Filip Vasiljevi, Goran Mikovi, Nikola Faculty of Electrical Engineering and Computing LABUST Laboratory for Underwater Systems and Technologies University of Zagreb Unska 3 Zagreb Croatia Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Unska 3 Zagreb Croatia

In order to achieve long-term autonomy after deployment, a method of energy sharing within a heterogeneous swarm of marine robots was devised and implemented. This paper describes hardware and software solutions as well as guidance and control algorithms developed with the goal of allowing powerful energy-rich overactuated surface platforms to approach, dock, and wirelessly recharge less mobile sensor-rich agents upon request using visual servoing. The basic image processing algorithm uses data acquired by the Microsoft Kinect sensor alternating between RGB and infra-red camera modes, depending on lighting conditions. The full search and docking procedure developed for long-term operation is described. The results of a series of experiments done both in an indoor testbed and in realistic outdoor conditions are discussed and some goals for future work are given. © 2018

关键词： Autonomous agents

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