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Single-Loop Deadbeat Predictive control Framework for Uncertain SPMSM Drives With Disturbance Observation

IEEE Transactions on Transportation Electrification 2025年

作者： Jiang, Fuxi Wang, Siqi Guo, Yuhao Cheng, Zhe Ye, Jie Cheng, Shanmei Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology School of Optical and Electronic Information Wuhan430074 China

To mitigate the detrimental effects of parameter perturbations and external load torque on the accuracy of speed and current tracking control in surface-mounted permanent magnet synchronous motor (SPMSM) drive systems, while avoiding the complexities inherent in traditional speed-current series control architectures, this paper presents a single-loop deadbeat predictive control (SDPC) framework that incorporates online disturbance observation. The control input voltage vector is directly computed using an SDPC controller in conjunction with a set of discrete-time disturbance observers (DDOBs). This proposed methodology offers two notable advantages over existing research: (i) it substantially reduces the number of adjustable controller parameters, requiring only the tuning of the observer bandwidth and the speed scaling gain, which enhances its practicality for engineering applications;and (ii) the disturbance estimation and compensation mechanism utilizing DDOBs significantly improves the robustness of the SPMSM system. Furthermore, the SDPC framework ensures that the system maintains satisfactory transient and steady-state tracking performance in response to reference signals. Experimental comparisons validate both the effectiveness and superiority of the proposed method. © 2015 IEEE.

关键词： Permanent magnets

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Niobium telluride absorber for a mode-locked vector soliton fiber laser

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Science China(Physics,Mechanics & Astronomy) 2023年第5期66卷 130-138页

作者： XinXin Shang NanNan Xu Jia Guo Shuo Sun HuaNian Zhang SWageh Ahmed AAl-Ghamdi Han Zhang DengWang Li Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Shandong Provincial Key Laboratory of Optics and Photonic DeviceSchool of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of Microscale Optoelectronics Collaborative Innovation Center for Optoelectronic Science&TechnologyKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen Key Laboratory of Micro-Nano Photonic Information TechnologyGuangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)Shenzhen UniversityShenzhen 518060China School of Physics and Optoelectronic Engineering Shandong University of TechnologyZibo 255049China Department of Physics Faculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Niobium telluride(NbTe_(2)),an emerging transition metal dichalcogenide material,has been theoretically predicted to have nonlinear absorption properties and excellent optical ***,only a few studies of the utilization of NbTe_(2)in ultrafast photonics have been *** this work,a NbTe_(2)-based saturable absorber(SA)was applied in an erbium-doped fiber as a mode-locked device,and a vector soliton based on NbTe_(2)was obtained for the first ***_(2)-PVA film SA was successfully prepared by the liquid-phase exfoliation and spin coating methods,with a modulation depth of up to 10.87%.The nonlinear absorption coefficient of NbTe_(2)-based SA film tested through the open-aperture Z-scan laser measurement is 0.62×10^(−11) m/W.A conventional soliton with a pulse duration of 858 fs was generated using NbTe_(2)-based SA,which was demonstrated to be a kind of polarization-locked vector soliton in further *** experimental results reveal the nonlinear optical properties of NbTe_(2)and broaden its applications in ultrafast photonic devices.

关键词： niobium telluride saturable absorber mode-locked pulse fiber laser

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When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo

When Epipolar Constraint Meets Non-local Operators in Multi-...

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International Conference on Computer Vision (ICCV)

作者： Tianqi Liu Xinyi Ye Weiyue Zhao Zhiyu Pan Min Shi Zhiguo Cao Ministry of Education School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Learning-based multi-view stereo (MVS) method heavily relies on feature matching, which requires distinctive and descriptive representations. An effective solution is to apply non-local feature aggregation, e.g., Transformer. Albeit useful, these techniques introduce heavy computation overheads for MVS. Each pixel densely attends to the whole image. In contrast, we propose to constrain nonlocal feature augmentation within a pair of lines: each point only attends the corresponding pair of epipolar lines. Our idea takes inspiration from the classic epipolar geometry, which shows that one point with different depth hypotheses will be projected to the epipolar line on the other view. This constraint reduces the 2D search space into the epipolar line in stereo matching. Similarly, this suggests that the matching of MVS is to distinguish a series of points lying on the same line. Inspired by this point-toline search, we devise a line-to-point non-local augmentation strategy. We first devise an optimized searching algorithm to split the 2D feature maps into epipolar line pairs. Then, an Epipolar Transformer (ET) performs non-local feature augmentation among epipolar line pairs. We incorporate the ET into a learning-based MVS baseline, named ET-MVSNet. ET-MVSNet achieves state-of-the-art reconstruction performance on both the DTU and Tanks-and-Temples benchmark with high efficiency. Code is available at https://***/TQTQliu/ET-MVSNet.

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Semi-Supervised Generalized Source-Free Domain Adaptation (SSG-SFDA)

Semi-Supervised Generalized Source-Free Domain Adaptation (S...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jiayu An Changming Zhao Dongrui Wu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

Continual learning aims to learn on a sequence of new tasks while maintaining the performance on previous tasks. Source-free domain adaptation (SFDA), which adapts a pretrained source model to a target domain, is useful in protecting the source domain data privacy. Generalized SFDA (G-SFDA) combines continual learning and SFDA to achieve outstanding performance on both the source and the target domains. This paper proposes semi-supervised G-SFDA (SSG-SFDA) for domain incremental learning, where a pre-trained source model (instead of the source data), few labeled target data, and plenty of unlabeled target data, are available. The goal is to achieve good performance on all domains. To cope with domain-ID agnostic, SSG-SFDA trains a conditional variational auto-encoder (CVAE) for each domain to learn its feature distribution, and a domain discriminator using virtual shallow features generated by CVAE to estimate the domain ID. To cope with catastrophic forgetting, SSG-SFDA uses soft domain attention to improve the sparse domain attention in G-SFDA. To cope with insufficient labeled target data, SSG-SFDA uses MixMatch to augment the unlabeled target data and better exploit the few labeled target data. Experiments on three datasets demonstrated the effectiveness of SSG-SFDA.

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Demand-Side Frequency control in Power Network Based on Multi-Agent Deep Reinforcement Learning

Demand-Side Frequency Control in Power Network Based on Mult...

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International Conference on Industrial Artificial intelligence (IAI)

作者： Xianggang Liu Zhi-Wei Liu Ming Chi Yifan Zhang Key Laboratory of Image Processing and Intelligent Control Ministry of Education College of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

The integration of renewable energy sources into the power grid has led to new challenges in maintaining the stability of the system frequency. This paper proposes a novel approach to address the Optimal Demand Side Frequency control (ODFC) problem using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method. The proposed method models the ODFC problem as a Markov game, with centralized training based on multi-agent cooperative self-learning and associative storage service. In the decentralized execution stage, each agent independently outputs control actions to the controlled plant using local observations. Numerical simulations show that the proposed method effectively addresses the ODFC problem with superior performance compared to traditional methods.

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MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition

arXiv

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arXiv 2023年

作者： Wang, Xiang Zhang, Shiwei Qing, Zhiwu Gao, Changxin Zhang, Yingya Zhao, Deli Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China

Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they generally suffer from two limitations: i) the matching procedure between local frames tends to be inaccurate due to the lack of guidance to force long-range temporal perception;ii) explicit motion learning is usually ignored, leading to partial information loss. To address these issues, we develop a Motion-augmented Long-short Contrastive Learning (MoLo) method that contains two crucial components, including a long-short contrastive objective and a motion autodecoder. Specifically, the long-short contrastive objective is to endow local frame features with long-form temporal awareness by maximizing their agreement with the global token of videos belonging to the same class. The motion autodecoder is a lightweight architecture to reconstruct pixel motions from the differential features, which explicitly embeds the network with motion dynamics. By this means, MoLo can simultaneously learn long-range temporal context and motion cues for comprehensive few-shot matching. To demonstrate the effectiveness, we evaluate MoLo on five standard benchmarks, and the results show that MoLo favorably outperforms recent advanced methods. The source code is available at https://***/alibaba-mmai-research/MoLo. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Neural-Network-Based Nonlinear Model Predictive Tracking control of a Pneumatic Muscle Actuator-Driven Exoskeleton

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1478-1488页

作者： Yu Cao Jian Huang IEEE Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Pneumatic muscle actuators(PMAs)are compliant and suitable for robotic devices that have been shown to be effective in assisting patients with neurologic injuries,such as strokes,spinal cord injuries,etc.,to accomplish rehabilitation ***,because PMAs have nonlinearities,hysteresis,and uncertainties,etc.,complex mechanisms are rarely involved in the study of PMA-driven robotic *** this paper,we use nonlinear model predictive control(NMPC)and an extension of the echo state network called an echo state Gaussian process(ESGP)to design a tracking controller for a PMA-driven lower limb *** dynamics of the system include the PMA actuation and mechanism of the leg orthoses;thus,the system is represented by two nonlinear uncertain *** facilitate the design of the controller,joint angles of leg orthoses are forecasted based on the universal approximation ability of the ESGP.A gradient descent algorithm is employed to solve the optimization problem and generate the control *** stability of the closed-loop system is guaranteed when the ESGP is capable of approximating system *** and experiments are conducted to verify the approximation ability of the ESGP and achieve gait pattern training with four healthy subjects.

关键词： Echo state Gaussian process model predictive control neural network pneumatic muscle actuators-driven exoskeleton

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Research on Metaverse Multi-person Linkage Using Mobile Edge Computing Based on Extended Reality Under the Immersive Experience of Zhijiang Peace Culture Memorial Hall 16th

Research on Metaverse Multi-person Linkage Using Mobile Edge...

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16th EAI International Conference on Wireless Internet, WiCON 2023

作者： Liu, Yiwen Fu, Jinrong Yan, Haobo Gao, Yanxia Peng, Ling Qu, Taiguo School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (纸本)9783031580529

This study aims to deeply explore the impact of mobile edge computing based on extended reality technology on the multi-person linkage of the Zhijiang Peace Culture Memorial Hall under the immersive experience. In the part of research background and significance, it discusses the rise of the application of XR technology in the field of culture and education, emphasizing the importance of education on the history of revolution and its value in the social sense. Then, it expounds the core topic of this research aimed at integrating XR technology with education on the history of revolution, and presenting visitors with more realistic and immersive historical scenes by creating an immersive experience of multi-person linkage. The use of these technologies enables visitors to transcend time and space barriers, directly participate in historical events, and deeply appreciate the intrinsic value of red culture. In order to achieve multi-person linkage, this study adopts mobile edge computing technology to ensure that multiple visitors can realize real-time interaction in the virtual scene and jointly build a collective experience of the Metaverse. This research has achieved positive results in the fields of XR technology application, education on the history of revolution, and mobile edge computing. It provides a useful reference for the modernization and upgrading of the Zhijiang Peace Culture Memorial Hall, and also provides a new paradigm for the cultural promotion of multi-person linkage experience in Metaverse. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Mobile edge computing

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Adaptive Event-triggered control with Sampled Transmitted Output and controller Dynamics

arXiv

引用

arXiv 2024年

作者： Zuo, Gewei Zhu, Lijun School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430072 China Key Laboratory of Imaging Processing and Intelligence Control

The event-triggered control with intermittent output can reduce the communication burden between the controller and plant side over the network. It has been exploited for adaptive output feedback control of uncertain nonlinear systems in the literature, however the controller must partially reside at the plant side where the computation capacity is required. In this paper, all controller components are moved to the controller side and their dynamics use sampled states rather than continuous one with the benefit of directly estimating next triggering instance of some conditions and avoiding constantly checking event condition at the controller side. However, these bring two major challenges. First, the virtual input designed in the dynamic filtering technique for the stabilization is no longer differentiable. Second, the plant output is sampled to transmit at plant side and sampled again at controller side to construct the controller, and the two asynchronous samplings make the analysis more involving. This paper solves these two issues by introducing a new state observer to simplify the adaptive law, a set of continuous companion variables for stability analysis and a new lemma quantifying the error bound between actual output signal and sampled transmitted output. It is theoretically guaranteed that all internal signals in the closed-loop system are semiglobally bounded and the output is practically stabilized to the origin. Finally, the numerical simulation illustrates the effectiveness of proposed scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： controllers

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DisGNet: A Distance Graph Neural Network for Forward Kinematics Learning of Gough-Stewart Platform

arXiv

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arXiv 2024年

作者： Zhu, Huizhi Xu, Wenxia Huang, Jian The Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan430205 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

In this paper, we propose a graph neural network, DisGNet, for learning the graph distance matrix to address the forward kinematics problem of the Gough-Stewart platform. DisGNet employs the k-FWL algorithm for message-passing, providing high expressiveness with a small parameter count, making it suitable for practical deployment. Additionally, we introduce the GPU-friendly Newton-Raphson method, an efficient parallelized optimization method executed on the GPU to refine DisGNet’s output poses, achieving ultra-high-precision pose. This novel two-stage approach delivers ultra-high precision output while meeting real-time requirements. Our results indicate that on our dataset, DisGNet can achieves error accuracys below 1mm and 1deg at 79.8% and 98.2%, respectively. As executed on a GPU, our two-stage method can ensure the requirement for real-time computation. Codes are released at https://***/FLAMEZZ5201/DisGNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Newton-Raphson method

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