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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Xiang, Kexin Wang, Weiqun Hou, Zeng-Guang Zhang, Chutian Wang, Jiaxing Shi, Weiguo Jiao, Yuze Lin, Tianyu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The School of Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China Macau Institute of Systems Engineering Macau University of Science and Technology China The CASIAMUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665481090

Accurate rehabilitation assessments are essential for designing effective rehabilitation methods and helping patients recover better. It's well known that commonly used scale assessment methods for neurorehabilitation suffer from the issue of subjectivity, thus investigation of objective assessment methods is very necessary. Muscle synergy analysis can be uesd to assess limb motor functions from the perspective of neuromuscular control. In this paper, a method for evaluation of human lower limb motor functions based on muscle synergy analysis is presented. Muscle synergy modules are designed using surface electromyography (sEMG) signals of the subjects' lower limbs by non-negative matrix factorizations (NMF). By comparing the cosine similarities of these synergy modules, it can be seen that muscle synergies of healthy subjects and patients are significantly different, while they are similar among healthy subjects. Therefore, a reference synergy module (RSM) is designed by averaging the muscle synergy modules for healthy subjects, and the similarities can be calculated by comparing the synergy modules for healthy subjects or patients with the RSM. In the experiment carried out in this study, average similarities of the three synergy modules for healthy subjects are respectively 0.97166, 0.87368 and 0.84932, and on the other hand, the average similarities for the three synergy modules for patients are respectively 0.59979, 0.56426 and 0.69042. Therefore, the similarities for healthy subjects are much higher than those for SCI patients, which denotes that the similarity between an individual synergy module and the RSM can be used as an objective assessing index for evaluating patients' motor function. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Protecting Multiple Types of Privacy Simultaneously in EEG-Based Brain-Computer Interfaces

Protecting Multiple Types of Privacy Simultaneously in EEG-B...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lubin Meng Xue Jiang Tianwang Jia Dongrui Wu Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs.

关键词： Training Privacy Data privacy Accuracy Perturbation methods Machine learning Electroencephalography Brain-computer interfaces Protection Spectrogram

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Global Asymptotic Synchronization of Coupled Neural Networks with Reaction Diffusions and Unbounded Time-varying Delays

Global Asymptotic Synchronization of Coupled Neural Networks...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yun Xing Yin Sheng The Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This article investigates global asymptotic synchronization of coupled neural networks with reaction diffusions and unbounded time-varying delays (RDUDCNNs). Through designing a centralized adaptive controller and corresponding updating laws of time-varying control gains, under two different upper bound of control gains, an asymptotic convergence lemma under unbounded time-varying delays and the Barbarat lemma are used to derive global asymptotic synchronization of RDUDCNNs, respectively. The effectiveness of the obtained conclusion is verified through a numerical simulation.

关键词： Upper bound Automation Neural networks Numerical simulation Delays Synchronization Convergence

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Precise orbit determination for TH02-02 satellites based on BDS3 and GPS observations

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Chinese Journal of Aeronautics 2023年第5期36卷 475-485页

作者： Houzhe ZHANG Bing JU Defeng GU Ying LIU Kai SHAO Xiaojun DUAN Zhiyong HUANG College of Science National University of Defense TechnologyChangsha 410073China National Key Laboratory of Science and Technology on Aerospace Flight Dynamics Beijing Aerospace Control CenterBeijing 100094China MOE Key Laboratory of TianQin Mission TianQin Research Center for Gravitational PhysicsFrontiers Science Center for TianQinCNSA Research Center for Gravitational WavesSun Yat-sen University(Zhuhai Campus)Zhuhai 519082China School of Artificial Intelligence Sun Yat-sen University(Zhuhai Campus)Zhuhai 519082China School of Physics and Astronomy Sun Yat-sen University(Zhuhai Campus)Zhuhai 519082China Information Engineering University Zhengzhou 450001China

The Tianhui-202(TH02-02)satellite formation,as a supplement to the microwave mapping satellite system Tianhui-201(TH02-01),is the first Interferometric Synthetic Aperture Radar(InSAR)satellite formation-flying system that supports the tracking of BeiDou global navigation Satellite system(BDS3)new B1C and B2a ***,the twin TH02-02 satellites also support the tracking of Global Positioning System(GPS)L1&L2 and BDS B1I&B3I *** the spaceborne receiver employs two independent boards to track the Global Navigation Satellite System(GNSS)satellites,we design an orbit determination strategy by estimating independent receiver clock offsets epoch by epoch for each GNSS to realize the multi-GNSS data fusion from different *** performance of the spaceborne receiver is evaluated and the contribution of BDS3 to the kinematic and reduced-dynamic Precise Orbit Determination(POD)of TH02-02 satellites is *** tracking data onboard shows that the average number of available BDS3 and GPS satellites are 8.7 and 9.1,*** carrier-to-noise ratio and carrier phase noise of BDS3 B1C and B2a signals are comparable to those of ***,strong azimuth-related systematic biases are recognized in the pseudorange multipath errors of B1C and *** pseudorange noise of BDS3 signals is better than that of GPS after eliminating the multipath errors from specific *** the GPS-based reduced-dynamic orbit with single-receiver ambiguity fixing technique as a reference,the results of BDS3-only and BDS3+GPS combined POD are *** Root Mean Square(RMS)of orbit comparison of BDS3-based kinematic and reduced-dynamic POD with reference orbit are better than 7 cm and 3 cm in three-Dimensional direction(3D).The POD performance based on B1C&B2a data is comparable to that based on B1I&*** precision of BDS3+GPS combined kinematic orbit can reach up to 3 cm(3D RMS),which has a more than 25%improvement relative to the GPS-only *** addi

关键词： BDS3 Multi-GNSS Precise orbit determination spaceborne GNSS receiver TH02-02

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Adaptive control of an axially moving beam with actuator failure

Adaptive control of an axially moving beam with actuator fai...

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第43届中国控制会议

作者： Xueli Liu Shuang Zhang Nan Feng Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of EducationUniversity of Science and Technology Beijing Institute of Artificial Intelligence University of Science and Technology Beijing

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper introduces an adaptive boundary control scheme proposed for moving beam systems,considering both actuator faults and boundary disturbances. The adaptive control law is constructed to reduce the vibration of the moving beam by using backstepping technique and an auxiliary variable. The examination of stability of the moving beam system,incorporating both actuator fault and boundary disturbance,is conducted through the application of the Lyapunov energy function ***,the proposed adaptive control scheme is validated for its effectiveness through simulation analyses.

关键词： Adaptive control actuator failure moving beam

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Q-learning-based space target selection for CNS/INS integrated navigation

Q-learning-based space target selection for CNS/INS integrat...

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Chinese control and Decision Conference, CCDC

作者： Dong Wang Jing Yang Kai Xiong School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

To solve the problem that intermittent celestial observation will hamper the navigation accuracy of celestial and inertial integrated navigation system (CNS/INS), a Q-learning-based space target selection method is proposed. The visibility situation of space targets is analyzed under given flight mission, which lays the foundation for subsequent pointing optimization. Q-learning algorithm is employed to optimize the sequence of visible space target. The reward function is designed based on the trace of Fisher information matrix and the rotation angle of optical axis which could make a synthetic balance between navigation accuracy and rotation cost. By setting the optimized pointing sequence to CNS/INS integrated navigation system, unintermittent celestial observation can be achieved to guarantee filtering performance with relatively low rotation cost, which has a certain value of practical engineering application. Comparative simulation experiments demonstrate the effectiveness of the proposed method in terms of navigation accuracy and rotation cost.

关键词： Optical filters Accuracy Costs Q-learning Navigation Filtering space missions

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Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces

arXiv

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arXiv 2024年

作者： Meng, Lubin Jiang, Xue Jia, Tianwang Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs. To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs. © 2024, CC BY.

关键词： Differential privacy

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A Novel Dynamic Peer-to-Peer Carbon Right Sharing Scheme for Microgrid Clusters

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IEEE Transactions on Smart Grid 2025年

作者： Zhou, Wei Lai, Jingang Li, Xi Zeng, Zhigang School of Artificial Intelligence and Automation China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan430074 China

In this paper, a novel four-level distributed game decision-making framework of dynamic peer-to-peer (P2P) carbon emission right (CER) sharing is proposed for microgrid clusters (MGCs), which consists of four phases: exploration, selection, equilibrium and correction. Firstly, in the exploration stage, the tradable information is published by microgrids (MGs) and an initial set of tradable options is constructed. Secondly, in the selection stage, bilateral transaction coefficients are calculated according to the deficit and surplus of CERs in the P2P carbon market, and then an optimal sharing matching scheme of CERs is designed to reduce invalid transactions. Thirdly, in the equilibrium stage, a P2P carbon right sharing strategy based on the Stackelberg game is proposed to realize the dynamic change in carbon prices and the flexible conversion of master-slave roles in P2P carbon trading, which can promote the popularity of carbon market. Fourthly, in the correction stage, a carbon emission right balancer (CERB) is developed to avoid the imbalance of CERs, and then a billing scheme including incentives and penalties is established to achieve the benefit redistribution after P2P carbon trading. In the end, numerical results illustrate the effectiveness of the proposed multi-layer game decision-making framework for P2P carbon right sharing among MGs. © 2010-2012 IEEE.

关键词： carbon emission right balancer Microgrid cluster peer-to-peer carbon trading Stackelberg game

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Adaptive Neural Finite-Time Deployment of Heterogeneous Multi-agent Systems via a Cross-Species Bionic PDE-ODE Approach

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人工智能科学与工程 2025年第1期1卷 52-63页

作者： Jingtao MAN Zhigang ZENG School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

For large-scale heterogeneous multi-agent systems(MASs)with cha-racteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel cross-species bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)***-fically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population *** coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered ***,by integrating adaptive neural control scheme with the aforementioned biological models,a"Flexible Neural Network"endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time ***,effectiveness of the developed approach is illustrated through a numerical example.

关键词： large-scale heterogeneous MASs cross-species bionic framework prac-tical finite-time deployment PDE-ODE approach adaptive neural con-trol

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A Novel Attitude controller for Hypersonic Aircraft Based on FR-PI2

A Novel Attitude Controller for Hypersonic Aircraft Based on...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Fan, Jiajun Li, Tianyi Guo, Xian Hao, Mingrui Sun, Mingwei College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811581540

Due to the uncertainties and various noises of the Hypersonic Aircraft(HA), traditional method of designing attitude controllers based on accurate models faces immense challenges. To solve those proposed urgent problems effectively, in this paper, a innovative data-driven RL algorithm called FR-PI2 is proposed for the task of Hypersonic Aircraft attitude control, wherein several key techniques are introduced. Firstly, Hypersonic Aircraft attitude control is transformed into a stochastic optimal control problem, and the numerical solutions of the proposed stochastic optimal control problem are obtained with a path-integral-based method, called Policy Improvement with Path Integrals(PI2). Secondly, a model-free policy parameterization method with PID controller is integrated into the PI2 algorithm to ensure a low dependency of the Hypersonic Aircraft system model. Thirdly, a brand-new sample filtration method is proposed to guarantee rapid convergence, and an online optimization technology called rolling optimization is applied to guarantee optimality and real-time performance. Two series of experiments are carried out and analyzed to demonstrate the outstanding performance of the FR-PI2 algorithm. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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