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Boosting-Based EMG Patterns Classification Scheme for Robustness Enhancement

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2013年第3期17卷 545-552页

作者： Li, Zhijun Wang, Baocheng Yang, Chenguang Xie, Qing Su, Chun-Yi S China Univ Technol Key Lab Autonomous Syst & Network Control Coll Automat Sci & Engn Guangzhou 510641 Guangdong Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Univ Plymouth Sch Comp & Math Plymouth PL4 8AA Devon England Shanghai Jiao Tong Univ Ruijin Hosp Dept Rehabil Med Shanghai 200240 Peoples R China

The high conventional accuracy of pattern recognition-based surface myoelectric classification in laboratory experiments does not necessarily result in high accessibility to practical protheses. An obvious reason is the effect of signals of untrained classes caused by the relatively small training dataset. In order to make the classifier robust to untrained classes, a classification scheme is developed based on boosting and random forest classifiers in this paper. Meanwhile, a threshold, the post probability of the prediction, is introduced as a balance (i.e., adjust) between the accurate classification and the rejection of the samples belonging to some untrained classes. The experiments are conducted to compare with other two schemes using linear discriminant analysis and support vector machines. Surface electromyogram signals, labeled with seven isometric movements, are collected from six healthy subjects' forearm. It is shown that the proposed scheme can reach up to about 92% accuracy in recognizing trained classes and 20% for untrained classes. Through adjusting the threshold, the accuracy of rejecting untrained classes reaches up to around 80%, with small decrease in recognizing trained classes (down to 80%). In the analysis of experiments' results, we also find that the proposed scheme has better error distribution among the classes.

关键词： Boosting electromyogram pattern recognition random forest

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Contact-Force Distribution Optimization and control for Quadruped Robots Using Both Gradient and Adaptive Neural networks

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IEEE TRANSACTIONS ON NEURAL networkS AND LEARNING systemS 2014年第8期25卷 1460-1473页

作者： Li, Zhijun Ge, Shuzhi Sam Liu, Sibang S China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou 510640 Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore Univ Elect Sci & Technol China Inst Robot Chengdu 610054 Peoples R China Univ Elect Sci & Technol China Inst Intelligent Syst & Informat Technol Chengdu 610054 Peoples R China

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots;the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

关键词： External wrench forces distribution motion/force control quadruped robot

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Development of A Biofeedback Enhanced Multimedia Game

Development of A Biofeedback Enhanced Multimedia Game

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第28届中国控制与决策会议

作者： Huaiwei Wu Chenguang Yang Ruowei Wang Chun-Yi Su MOE Key Lab of Autonomous System and Network Control School of Automation Science and EngineeringSouth China University of Technology Zienkiewicz Centre for Computational Engineering Swansea University Department of Mechanical and Industrial Engineering Concordia University

ISBN: (纸本)9781467397155

As a frontier technology,biofeedback has been widely used for psychological treatment,control and many other human-computer interaction *** this paper,a multimedia game based on biofeedback technology is developed,including two main parts,the design of a brain computer interface(BCI) and the design of a multimedia *** the BCI design part,eletroencephlogram(EEG) signals are collected and sent to a processing module for *** EEG signals will be classified into two categories:movement or *** these classified results will be sent to the game process to control the action of a virtual car in real *** the second part,the design of a multimedia game via QTCreator is *** mainly use QTCreator's Graphics View Frame to develop the *** last we will introduce how to combine MATlab,SCAN4.5 and QTCreator together to play the game with biofeedback.

关键词： Development of A Biofeedback Enhanced Multimedia Game

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Resilient Adaptive Event-Triggered H-8 Fuzzy Filtering for Cyber-Physical systems Under Stochastic-Sampling and Denial-of-Service Attacks

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IEEE TRANSACTIONS ON FUZZY systemS 2023年第1期31卷 278-292页

作者： Xie, Xuhuan Hu, Songlin Liu, Yonggui Li, Qinxue South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Carbon Neutral Nanjing 210023 Peoples R China Wuhan Univ Technol Hubei Key Lab Inland Shipping Technol Wuhan 430063 Peoples R China South China Univ Technol Sch Automation Sci & Engn Key Lab Autonomous Syst & Network Control Minist Educ Guangzhou 510641 Peoples R China Guangzhou Maritime Univ Sch Ship & Ocean Engn Guangzhou 510700 Peoples R China

This article is concerned with resilient adaptive event triggered H-infinity fuzzy filtering for a class of interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy-model-based cyber-physical systems (CPSs) under stochastic sampling and energy-constrained, non-periodic denial-of-service (DoS) attacks. The nonlinear plant with parameter uncertainties is represented as a class of IT2 T-S fuzzy systems, and a novel resilient adaptive event-triggered scheme (AETS) against stochastic sampling and DoS attacks is proposed. In the designing process of the fuzzy filter, a novel resilient switched IT2 T-S fuzzy filter that switches according to the DoS attacks is applied. Then, the switched stochastic delayed systems model with a favorable form is established for the filtering-error-system. Based on the Lyapunov-Krasovskii stability theory and switched stochastic delayed systems theory, the relaxed stability condition is derived, which can ensure that the filtering-error-system is stochastically exponentially stable (SES) where the decay rate is indicated, the maximum frequency of DoS attacks is revealed, and an H-infinity disturbance attenuation performance is guaranteed. Also, the code sign algorithm is further developed to implement the codesign of fuzzy filter and resilient AETS. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed strategy.

关键词： Stochastic processes Switches Denial-of-service attack Adaptive systems Symmetric matrices Uncertain systems Takagi-Sugeno model Cyber-physical systems (CPSs) denial-of-service (DoS) attacks interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model resilient adaptive event-triggered H-8 filtering stochastic sampling

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An EMG Enhanced Impedance and Force control Framework for Telerobot Operation in Space

An EMG Enhanced Impedance and Force Control Framework for Te...

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IEEE Aerospace Conference

作者： Ning Wang Chenguang Yang Michael R. Lyu Zhijun Li Department of Computer Science and Engineering The Chinese University of Hong Kong School of Computing and Mathematics Plymouth University Key Lab of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781479916191

Tele-operation is a merging point of modern developments in robotics and communications technologies. Both traditional applications (e.g., mining) and emerging domains (e.g., microsurgery) benefit from the advancement of tele-robotic systems. Combining a local human operator and a remote autonomous robot, the tele-robotics systems could optimally exploit both the intelligence of human operator and the automation of robot. In a tele-operation scenario, the exchange of force and position signals, i.e., haptic feedback, can greatly extend human operator's capability of conducting complicated work through the robot in a remote environment. However, long-range communications usually suffer from the time delay problem caused by the inherent characteristics of communication channels. Delayed transmission of haptic signals may lead to instability in the closed-loop telerobot control system. Although much effort has been made in the control community to overcome this difficulty, and many approaches such as wave scattering, passivity, and small gain theorem have been employed as possible solutions, stability in haptic telerobot control remains a challenge. It has been noted that the neural path of human being is also subject to transmission delay as well. We know that in the presence of time delay in sensory feedback pathways, human neural control can easily maintain stability and even to show superior manipulation skills in unstable interaction scenarios. It has been discovered and reported that the operation stability of human beings could be achieved by well adjusting the mechanical impedance, i.e., the resistance to imposed motion, which is largely contributed by the spring-like property of muscles. Being investigated in robotics community for decades, impedance control has shown great advantage in terms of safety and flexibility over conventional position or force control. However, only until very recently our attention has been attracted to transferring a human operator

关键词： impedance Electromyogram Human Robot Force Astronauts Force control muscles robotics

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Multi-stream adaptive 3D attention graph convolution network for skeleton-based action recognition

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APPLIED INTELLIGENCE 2023年第12期53卷 14838-14854页

作者： Yu, Lubin Tian, Lianfang Du, Qiliang Bhutto, Jameel Ahmed South China Univ Technol Sch Automat Sci & Engn Guangzhou Peoples R China Minist Ind & Informat Technol Elect Res Inst 5 Guangzhou Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai Peoples R China SinoSingapore Int Joint Res Inst Guangzhou Peoples R China Key Lab Autonomous Syst & Network Control Minist Guangzhou Peoples R China Huanggang Normal Univ Sch Comp Huanggang Peoples R China

Action recognition methods based on spatial-temporal skeleton graphs have been applied extensively. The spatial and temporal graphs are generally modeled individually in previous approaches. Recently, many researchers capture the correlation information of temporal and spatial dimensions in spatial-temporal graphs. However, the existing methods have several issues such as 1. The existing modal graphs are defined based on the human body structure which is not flexible enough;2. The approach to extracting non-local neighborhood features is insufficiently powerful;3. Attention modules are limited to a single scale;4. The fusion of multiple data streams is not sufficiently effective. This work proposes a novel multi-stream adaptive 3D attention graph convolution network for skeleton-based action recognition that improves the aforementioned issues. The method utilizes an adaptive topology graph with an adaptive connection coefficient to adaptively optimize the topology of the graph during the training process according to the input data. An optimal high-order adjacency matrix is constructed in our work to balance the weight bias, which captures non-local neighborhood features precisely. Moreover, we design a multi-scale attention mechanism to aggregate information from multiple ranges, which makes the graph convolution focus on more efficient nodes, frames, and channels. To further improve the performance of the model, a novel multi-stream framework is proposed to aggregate the high-order information of the skeleton. The experiment results on the NTU-RGBD and Kinetics-Skeleton prove that our proposed method reveals better results than existing methods.

关键词： Graph convolution Convolutional Neural network Adaptive Attention module Action recognition

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ADRC based on modified ESO for nonlinear time-varying system with impulsive disturbance 43

ADRC based on modified ESO for nonlinear time-varying system...

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43rd Chinese control Conference (CCC)

作者： Li, Xiangyang Bai, Jianer Huang, Jian Wang, Bingbing Tian, Senping South China Univ Technol Sch Automat Sci & Engn Minist Educ Key Lab Autonomous Syst & Network Control Guangzhou 510641 Peoples R China Kunming Shipborne Equipment Res & Test Ctr Kunming 650051 Yunnan Peoples R China Changji Univ Aviat Coll Changji 831100 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

The extended state observer (ESO) is the core of Active disturbance rejection control (ADRC) methodology. The paper proposes a new modified ESO which can overcome the initial peaking phenomenon and improve to adapt the abrupt change in disturbance change and keep the control system stable and enough accuracy. The adjustable parameter in modified ESO can be set according to the desired ESO performance which is hard to satisfy by just adjusting the bandwidth omega(o) of ESO. Simulations show that the proposed ADRC based on modified ESO has the same stable tracking performance and more effective to overcome initial peaking phenomenon and adapt setpoint and disturbance abrupt change.

关键词： Active disturbance rejection control (ADRC) extended state observer (ESO) nonlinear time-varying system impulsive disturbance

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Teleoperation of Humanoid Baxter Robot Using Haptic Feedback

Teleoperation of Humanoid Baxter Robot Using Haptic Feedback

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International Conference on Multisensor Fusion and Information Integration for Intelligent systems (MFI)

作者： Ju, Zhangfeng Yang, Chenguang Li, Zhijun Cheng, Long Ma, Hongbin Univ Plymouth Ctr Robot & Neural Syst Plymouth PL4 8AA Devon England North Automat Control Technol Inst Taiyuan 030006 Peoples R China S China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou 510640 Guangdong Peoples R China Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China Beijing Inst Technol Sch Automat State Key Lab Intelligent Control & Decis Complex Beijing 100081 Peoples R China

ISBN: (纸本)9781479967315

This paper presents a teleoperation strategy, which is featured by haptic feedback. The teleoperation system is composed of a SensAble (R) Omni haptic device, set as the master and providing haptic feedback, and an anthropomorphic robot slave, which is embodied by the 7-DOF (degrees of freedom) robotic arm of the Baxter (R) robot. The haptic feedback enables a bilateral manipulation of the teleoperation system. The joint angles and Cartesian position of the stylus of the Omni device are sampled and transferred to the slave, determining its motion. Meanwhile a force, proportional to the amplitude of position error of the slave manipulator, is sent back to the master and applied to the stylus. Hereby, the operator can sense the motion of the Baxter robot and adjust its manipulator accordingly. The kinematics of the master and slave have been analysed and a workspace mapping has been realized. Two methods, direct angle mapping and CLIK (closed-loop inverse kinematics), are used to implement the manipulation of the slave in position-position mode. Two experiments have been designed and tested to verify the validity of the methods provided by this paper. The results of the experiments illustrate that the designed teleoperation system is feasible and effective.

关键词： Inverse kinematics

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Admission control for P2P-based Media Delivery network

Admission control for P2P-based Media Delivery Network

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Chinese control Conference (CCC)

作者： Shan Lu Baoqun Yin Dong Guo Key Lab of Network Communication System and Control Chinese Academy of Sciences Department of Automation University of Science and Technology of China Hefei 230027 China

With wider application of P2P-based Media Delivery network (P2P-based MDN), much work has been done to improve the system' performance and efficiency in the process of media contents sharing. In this paper, we first propose a specific partially observable Markov Decision Process (POMDP) model for admission control of P2P-based MDN. Based on this model, we provide the observation-based randomized policy to conduct admission control and optimize the policy by applying policy-gradient algorithm. Observation-based policy can promote the system's performance in real time aspect and policy optimizing can increase the accuracy of controller's judgments based on partial information. Admission strategy in the paper can save the cost in operating the system for media service providers. Bandwidth allocation policy is designed to reduce service delay and provide high-quality service. The comparison results of system's performances under different policies indicate that, partial service can utilize the system's resource in a better way.

关键词： Admission control Bandwidth Media Markov processes Servers Motion pictures Biological system modeling

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Quick Convex Hull-Based Rendezvous Planning for Delay-Harsh Mobile Data Gathering in Disjoint Sensor networks

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2021年第6期51卷 3844-3854页

作者： Liu, Xuxun Wang, Tian Jia, Weijia Liu, Anfeng Chi, Kaikai South China Univ Technol Coll Elect & Informat Engn Guangzhou 510641 Peoples R China South China Univ Technol Key Lab Autonomous Syst & Network Control Minist Educ Guangzhou 510641 Peoples R China Huaqiao Univ Coll Comp Sci & Technol Xiamen 361021 Peoples R China Univ Macau State Key Lab Internet Things Smart City Macau Peoples R China Cent South Univ Sch Informat Sci & Engn Changsha 410083 Peoples R China Zhejiang Univ Technol Sch Comp Sci & Technol Hangzhou 310023 Peoples R China

Sink mobility is a significant technique to improve the performance of wireless sensor networks (WSNs). Generally a mobile sink visits several rendezvous points (RPs), forming a trip tour for data collection. However, the low movement speeds of mobile sinks tend to incur serious data delivery delays. In this article, we propose a quick convex hull-based rendezvous planning (QCHBRP) scheme, which aims to not only achieve full connectivity for disjoint WSNs but also construct a shorter trip tour and minimize the data delivery latency accordingly. The trajectory formation of the mobile sink is based on a path skeleton, i.e., a near-convex hull, which is created by the quick determination of several special locations as RPs. The benefits of QCHBRP are threefold. First, it is especially designed for disjoint WSNs where sensor nodes are deployed in multiple isolated segments and the network connectivity is lost in advance. Second, it is suitable for delay-harsh applications which require short paths of the mobile sink. Third, it is of much lower computational complexity compared with existing methods. The extensive analysis and experiments validate the effectiveness and advantages of this new scheme in terms of connectivity cost and data delivery delay.

关键词： Wireless sensor networks Delays Data collection Trajectory Planning Task analysis Clustering algorithms Connectivity data gathering delivery latency minimization mobile sink rendezvous planning wireless sensor networks (WSNs)

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