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第三十九届中国控制会议

作者： Binkai Yue Shoukun Wang Zhihua Chen Kang Xu Junzheng Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology

The electric parallel six wheel-legged robot（EPSWLR） is characterized by heavy load and fast moving speed. But the body will shake and vibrate while passing through rough roads, which affects its stability. In order to solve this problem, the single-leg structure based on Stewart structure was equivalent to the impedance system composed of mass block, spring and damping in this paper. Due to changes in environmental forces and environmental impedance parameters caused by environmental changes, the traditional impedance control（IC） still causes force error at the foot end of robot and thus results in poor vibration isolation effect. Therefore, a new adaptive algorithm was proposed in this paper and added to IC algorithm to reduce the force error caused by environmental changes and thus improve the vibration isolation effect. In this paper, the characteristic equation of adaptive impedance control（AIC） algorithm was first obtained and the condition for system stability was calculated based on Routh-Hurwitz stability criterion. Finally, the stability of this system was verified. The simulation experiment combining MATLAB and Adams was designed and performed with EPSWLR. The effectiveness of AIC was proved by monitoring the changes in the force of single leg and the attitude of robot body.

关键词： Electric parallel six wheel-legged robot Impedance control Adaptive algorithm Stewart structure

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Nonparametric Different-Feature Selection Using Wasserstein Distance

Nonparametric Different-Feature Selection Using Wasserstein ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Wenbo Zheng Fei-Yue Wang Chao Gou State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Intelligent Systems Engineering Sun Yat-sen University

ISBN: (数字)9781728192284

ISBN: (纸本)9781728185361

In this paper, we propose a feature selection method that characterizes the difference between two kinds of probability distributions. The key idea is to view the feature selection problem as a sparsest k-subgraph problem that considers Wasserstein distance between the studied two probability distributions. Our method does not presume any specific parametric models on the data distribution and is non-parametric. It outperforms existing Kullback-Leibler divergence based approaches, since we do not require two distributions to overlap. This relaxation makes our method work in many problems in which Kullback-Leibler divergence based methods fail. We also design a fast calculation algorithm using dynamic programming. Our experimental results show that our method outperforms the current method in both computation accuracy and speed.

关键词： Heuristic algorithms Conferences Tools Feature extraction Probability distribution Dynamic programming Parametric statistics

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Robust exponential load frequency control for time delay power system considering wind power ⁎

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IFAC-PapersOnLine 2020年第2期53卷 12536-12541页

作者： Li Jin Xingchen Shang-Guan Yong He Chuan-Ke Zhang Lin Jiang Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom

The injection of intermittent wind power reduces the equivalent inertia of power systems, and therefore, the change rate of frequency deviation for the load frequency control (LFC) schemes is increased. LFC schemes employ communication channels to transmit signals, which introduces time delays resulting in badly dynamic performance. This paper presents a delay-dependent approach to obtain the robust load frequency controllers based on decay rate for a multi-area LFC scheme integrated with wind power. An index of decay rate related to settling time is introduced. For a preset delay upper bound, controller gains are optimized by maximizing the decay rate. Also, the controller gains can be designed under the desired decay rate while obtaining the allowable maximum delay margins. Case studies are based on the deregulated multi-area LFC system to verify the robustness of developed controller against inertia reduction. Moreover, the proposed method enables the frequency deviation to be restrained and eliminated within a few seconds.

关键词： Load frequency control wind power communication delay decay rate

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Switching Method Based Load Frequency control for Power System with Energy-Limited DoS Attacks ⁎

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IFAC-PapersOnLine 2020年第2期53卷 13508-13513页

作者： Xingchen Shang-Guan Li Jin Yong He Chuan-Ke Zhang Lin Jiang Joseph William Spencer Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom

A load frequency control (LFC) scheme for modern power systems employs an open communication network to transmit control/measurement signals. The usage of the open communication network in power system makes the LFC scheme more vulnerable to communication network attacks, for example, a denial-of-service (DoS) attack. This attack will prevent a certain amount of transmission of the signals so as to degrade the performance of LFC scheme, or even lead to instability of power system. Therefore, this paper concerns LFC scheme for single-area power system with energy-limited DoS attack based on switching method. Compared with the latest schemes only considering duration of a DoS attacks, the proposed LFC takes fully into account both the duration and attack frequency of the DoS attack. A switching LFC model for a single-area power system is firstly constructed based on the characteristic of periodical sampling and DoS attacks. Then, an exponential stability criterion is developed in terms of the duration and frequency of a DoS attack. Next, a feasible controller of LFC scheme is derived by solving linear matrix inequalities in the criterion. Finally, a detailed design algorithm of LFC scheme is presented for a known DoS attack or an unknown DoS attack. The effectiveness of the proposed LFC scheme is evaluated on a single-area power system under DoS attacks. The proposed LFC scheme is compared with a robust LFC scheme and an event-triggered H ∞ LFC scheme. The obtained contrasting results demonstrate that the proposed LFC scheme can defend DoS attacks with limited energy, and can perform better control effect in the presence of load fluctuations.

关键词： Power system Load frequency control Open communication network Switching system DoS attacks Exponential stability

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Spiking Neural Network for Intra-cortical Brain Signal Decoding

arXiv

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arXiv 2025年

作者： Yang, Song Fu, Haotian Zhang, Herui Zhang, Peng Li, Wei Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based approaches have high computational cost. To improve both the decoding accuracy and efficiency, this paper proposes a spiking neural network (SNN) for effective and energy-efficient intra-cortical brain signal decoding. We also propose a feature fusion approach, which integrates the manually extracted neural activity vector features with those extracted by a deep neural network, to further improve the decoding accuracy. Experiments in decoding motor-related intra-cortical brain signals of two rhesus macaques demonstrated that our SNN model achieved higher accuracy than traditional artificial neural networks;more importantly, it was tens or hundreds of times more efficient. The SNN model is very suitable for high precision and low power applications like intracortical brain-computer interfaces. © 2025, CC BY.

关键词： Deep neural networks

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Asymmetric Barrier Function-based Adaptive control of a Four-Wheel-Steering Mobile Robot*

Asymmetric Barrier Function-based Adaptive Control of a Four...

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IEEE Region 10 International Conference TENCON

作者： Yuanlong Xie Liquan Jiang Jie Meng Shuting Wang Shiqi Zheng Hao Wu School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China School of Automation China University of Geosciences Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9781728184555

ISBN: (纸本)9781728184562

Four-wheel-steering mobile robots (FMR) are extensively-adopted for manufacturing applications. However, the robust trajectory tracking of FMR is hard to achieve due to the complex disturbances. For addressing the challenge, an asymmetric barrier function-based adaptive control (ABFAC) method is presented here for obtaining a robust direct yaw moment control scheme for the FMR. The praiseworthy features of the proposed ABFAC method are twofold: (a) It does not need the information concerning the upper boundary information of the unknown uncertainties; (b) By introducing the barrier function, the output signals are guaranteed to be within the desired neighborhood since the sliding mode gains will grow once the disturbance derivatives increase. In this context, the proposed ABFAC method drives the resultant trajectory tracks the variation tendency of the disturbances, guaranteeing robust closed-loop responses. The global stability of the FMR can be ensured theoretically. Finally, experimental results of real-time FMR are provided to validate the applicability of our ABFAC method.

关键词： Asymptotic stability Trajectory tracking Stability analysis Trajectory Mobile robots Adaptive control Convergence

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A Simulation-based Online Evolutionary Algorithm for Combat in StarCraft II

A Simulation-based Online Evolutionary Algorithm for Combat ...

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International Conference on intelligent Human-Machine systems and Cybernetics, IHMSC

作者： Yongfeng Liu Changhe Li Sanyou Zeng School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (数字)9781728165172

ISBN: (纸本)9781728165189

Real-time strategy (RTS) games have become one of the hotspots in the field of artificial intelligence research due to the large search space, long-term planning, and real-time constraint. In view of the fact that most of the current research on solving the RTS combat problem uses offline training methods, and these methods may need a lot of training time, this work uses an evolutionary algorithm (EA) to directly optimize the units' action sequences online. In order to solve the problems of repetitive actions caused by the neutral area and the size correlation caused by cooperation between units, three search operators are proposed. It is shown that this method can effectively solve the combat problem in RTS games.

关键词： Games Genomics Bioinformatics Sociology Statistics Data models Springs

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A Parallel Education Based intelligent Tutoring systems Framework

A Parallel Education Based Intelligent Tutoring Systems Fram...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Jing, Sifeng Tang, Ying Liu, Xiwei Gong, Xiaoyan Cui, Wei Liang, Joleen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States Squirrel Ai Learning Shanghai200030 China

ISBN: (纸本)9781728168531

although online education has improved efficiency of learners' access to high-quality educational resources, realtime interaction between instructors and learners have not yet been achieved in online personalized learning. intelligent Tutoring systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed. © 2020 IEEE.

关键词： Computer aided instruction

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K-9 Artificial Intelligence Education in Qingdao: Issues, Challenges and Suggestions

K-9 Artificial Intelligence Education in Qingdao: Issues, Ch...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Gong, Xiaoyan Tang, Ying Liu, Xiwei Jing, Sifeng Cui, Wei Liang, Joleen Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100084 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States Squirrel Ai Learning Shanghai200030 China

ISBN: (纸本)9781728168531

Nowadays, AI education from Kindergarten to 9th grade(K-9) is in full swing in China, but many challenges exist, such as fragmented AI curricula, ineffective teaching tools, and uneven educational resources in urban and rural areas, etc. So this paper presents an in-depth study of the current status of K-9 AI education in Qingdao area through questionnaires, expert discussions, and field visits to sort out existing problems and then put forward corresponding advice and suggestions. Collected data is then analyzed from the perspectives of government, schools, teachers, students and parents, respectively. Results show that AI-related educational activities have been carried out in Qingdao area to improve students' AI literacy. But efforts are still needed to make such education more systematic, standardized, and personalized. Finally the paper made a list of recommendations corresponding to these needed efforts. © 2020 IEEE.

关键词： Curricula

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Design of audio to image cross-modal learning and generation based on single-layer CoPt spin-orbit torque devices

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Journal of Magnetism and Magnetic Materials 2025年 629卷

作者： Qian, Likun Yang, Liu Zuo, Chao Tao, Ying Li, Wendi Jin, Fang Li, Huihui Dong, Kaifeng School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China Beijing Superstring Academy of Memory Technology Beijing100176 China

Despite remarkable achievements in neural network applications using spin–orbit torque (SOT) devices, current research predominantly focuses on unimodal classification tasks, while cross-modal learning tasks often suffer from suboptimal generation quality. To address this limitation, we employ generative adversarial networks (GANs) based on CoPt-SOT to achieve cross-modal learning and generation from speech to handwritten digit images. Initially, we explore the field-free switching characteristics of single-layer CoPt devices, developing spin-based implementations of Scaled Rectified Linear Unit (SReLu), Sigmoid, and Tanh neuronal functions. Simultaneously, we leverage the nonvolatile multistate characteristics of CoPt devices to realize excitatory-inhibitory synaptic plasticity. Subsequently, for the first time, we construct half-spin and full-spin GAN networks using these spin-based neurons and synapses, enabling cross-modal learning and generation between speech and image domains. Finally, we evaluate the performance of these networks through handwritten digit recognition tasks, achieving impressive recognition accuracies of 93.78 % and 88.61 % for half-spin and full-spin implementations, respectively. Notably, this work overcomes the existing bottleneck in SOT device applications, which have been largely confined to unimodal classification tasks, and demonstrates significant potential for expanding the scope of SOT-based technologies. © 2025 Elsevier B.V.

关键词： Generative adversarial networks

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