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IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)

作者： Qiuyi Chen Panagiotis Tsilifis Jaime Renedo Anglada Department of Mechanical Engineering University of Maryland College Park MD USA Robotics AI & Computer Vision Group GE Vernova Advanced Research Niskayuna NY USA Electrical Systems GE Vernova Advanced Research Niskayuna NY USA

ISBN: (数字)9798331520748

ISBN: (纸本)9798331520755

The rapid growth of offshore wind energy needs robust condition monitoring to ensure the reliability and efficiency of direct-drive permanent magnet synchronous generators (PMSGs). Demagnetization, a critical fault in these generators, can severely impact performance and increase operational costs, especially in harsh marine environments. Traditional diagnostic techniques often struggle to detect subtle magnetic property changes under varying load conditions. This paper presents an innovative framework for demagnetization detection in PMSGs, leveraging the Electrical Multi-phase Imbalance Separation Technique (eMIST) combined with machine learning models. Using a dataset from offshore wind turbines, including simulated faulty conditions, the proposed methodology enhances anomaly detection by isolating imbalance signatures and correlating them with key operational parameters. Gaussian Process Regression (GPR) is employed to predict anomalies, offering high accuracy and confidence in fault classification. Results demonstrate the approach's ability to identify early-stage demagnetization, enabling predictive maintenance, reducing downtime, and improving the economic viability of offshore wind farms.

关键词： Costs Accuracy Wind energy Machine learning Gaussian processes Wind farms Generators Wind turbines Demagnetization Anomaly detection

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Understanding Connection between PMP and HJB equations from the Perspective of Hamilton Dynamics

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： Zhang, Xiangteng Lyu, Yao Li, Shengbo Eben Duan, Jingliang Zhan, Guojian Liu, Chang Cheng, Bo Li, Keqiang Tsinghua University School of Vehicle and Mobility Beijing100084 China University of Science and Technology Beijing School of Mechanical Engineering China Peking University Department of Advanced Manufacturing and Robotics Beijing100871 China Peking University College of Engineering Beijing100871 China

Reinforcement learning (RL) is widely used to tackle optimal control problems, with optimality conditions as the principle of algorithm design. Two key optimality conditions are the Pontryagin Maximum Principle (PMP) and the Hamilton-Jacobi-Bellman (HJB) equation. The relationship between these conditions is vital for developing effective policy learning algorithms. Existing studies mainly focus on their relationship in the open-loop optimality, but this property cannot be directly extended to nonoptimal or closed-loop cases due to the absence of extreme condition and the existence of non-zero partial derivative term. This paper unifies the relationship between PMP and HJB equations in all cases by considering optimal control problems as nonholonomic Lagrange systems, and proves the intrinsic equivalence between value function and costate variable from the perspective of Hamilton dynamics. We redefine costate variable as Legendre transformation of state derivative in nonholonomic Lagrange systems, where the Weierstrass condition is selected as a constraint for optimal cases while fixed policy condition is chosen for nonoptimal cases. By utilizing the anti-symmetric property of canonical equations, we identify conservation properties in optimal control where symplectic form remains invariant across all cases. Additionally, we prove that the costate variable has the identical differential equation and boundary conditions as the partial derivative of value function with respect to state in both optimal and nonoptimal, open-loop and closed-loop cases. Numerical experiments are conducted to verify our theoretical results. This discovery can establish more readily available conservation conditions, thereby providing a high-level view angle on algorithm designs. © 2020 IEEE.

关键词： Lagrange multipliers

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Visual Sensor-Based Trajectory Multimodality Prediction via Anchor-Free Query Attention Network

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Wang, Ruiping Cheng, Jun Yu, Junzhi Nanyang Technological University School of Computer Science and Engineering Jurong West Singapore639798 Singapore Peking University College of Engineering Beijing100871 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

As a core component of intelligent surveillance and autonomous driving systems, visual sensor-based trajectory multimodality prediction can significantly improve their perception and decision-making capabilities. Numerous existing trajectory prediction methods are dedicated to enhance prediction performance. However, they still fail to effectively model the complex spatiotemporal interactions among pedestrians and trajectory multimodality. To address the above challenges, this article presents one new trajectory multimodality prediction method via anchor-free query-based attention network, which can more effectively capture spatiotemporal interactions and model trajectory multimodality. First, the initial trajectory proposal module employs target-centered query-based attention to capture complex spatiotemporal interactions and generate multiple trajectory proposals corresponding to the multiple modes of the future trajectory, which allows the model to use different interaction information when decoding trajectory points at different time steps. Second, the novel trajectory refinement module utilizes the learnable trajectory proposals to construct proposal-level interaction mechanisms to refine future trajectories. Experimental results conducted on ETH and UCY datasets demonstrate that the proposed model can provide the state-of-the-art prediction performance. © 1963-2012 IEEE.

关键词： Prediction models

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Novel method for robust bilateral filtering point cloud denoising

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Alexandria engineering Journal 2025年 127卷 573-585页

作者： Yang, Huan Wang, Wei Wang, Yue Wang, Peng College of Computer Science and Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Chongqing Nan'an400065 China School of Advanced Manufacturing Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Chongqing Nan'an400065 China Sevnce Robotics Co. Ltd Building 7 Phase II Internet Industrial Park Chongqing Liangjiang401123 China Big Data Institute BaoShan University No. 16 Yuanzheng Road Longyang District Yunnan Baoshan678000 China

Bilateral filtering for point cloud denoising relies on the normal of the points. However, normals are not inherent attributes of point clouds but are estimated using algorithms such as principal component analysis (PCA). Due to inaccuracies in the normals, bilateral filtering may lead to unexpected results, such as smoothing in sharp regions. This study addressed this issue by improving the accuracy of normals. Initially, PCA was employed to estimate the initial normals of the point cloud. The points were then categorized into edge and planar points by fitting a three-dimensional sphere. Subsequently, iterative weighted PCA was applied to refine the normals of the edge points. Finally, the improved normals were integrated into bilateral filtering to achieve point cloud denoising. Additionally, a robust estimator was used instead of a Gaussian function to compute the weights in the bilateral filtering. To assess and compare the performance of this algorithm with related ones, the mean square angular error (MSAE) and angular error distribution (AE) were employed to evaluate the accuracy of normal estimation, while the mean square error (MSE) and signal-to-noise ratio (SNR) were employed to assess the denoising performance. Results indicate that the proposed method yielded the most accurate normals compared to PCA, Jet, and VCM normal estimation algorithms. Moreover, when compared to algebraic point set surfaces (APSS), robust implicit moving least squares (RIMLS), anisotropic weighted locally optimal projection (AWLOP), bilateral filtering, and guided filtering point cloud denoising algorithms, the proposed method consistently achieved the smallest MSE and the highest SNR in most cases on the dataset used in this study. © 2025 The Authors

关键词： Principal component analysis

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Ultrahigh interfacial thermal conductance for cooling gallium oxide electronics using cubic boron arsenide

arXiv

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arXiv 2025年

作者： Zhou, Wenjiang Liang, Nianjie Xiao, Wei Tong, Zhaofei Tian, Fei Song, Bai Department of Energy and Resources Engineering Peking University Beijing100871 China School of Advanced Engineering Great Bay University Dongguan523000 China School of Materials Science and Engineering Sun Yat-sen University Guangdong Guangzhou510006 China Department of Advanced Manufacturing and Robotics Peking University Beijing100871 China National Key Laboratory of Advanced MicroNanoManufacture Technology Beijing100871 China

Gallium oxide (Ga2O3) has attracted significant interest for its unique potential especially in power electronics. However, its low and anisotropic thermal conductivity poses a major challenge for heat dissipation. Here, we explore an effective cooling strategy centering on the heterogeneous integration of β-Ga2O3 devices with cubic boron arsenide (cBAs), an emerging material with an ultrahigh thermal conductivity κ of ~1300 Wm-1K-1. Machine-learned potentials for representative β-Ga2O3/cBAs interfaces are trained, enabling accurate and efficient calculation of the interfacial thermal conductance G via nonequilibrium molecular dynamics. At 300 K, remarkable G values of 749±33 MWm-2K-1 and 824±35 MWm-2K-1 are predicted for Ga-As and O-B bonding across the interface, respectively, which are primarily attributed to the well-matched phonon density of states considering the similar Debye temperatures of β-Ga2O3 and cBAs. Moreover, finite-element simulations directly show a notable device temperature reduction when comparing cBAs with other substrates. The simultaneously ultrahigh κ and G highlight cBAs as an ideal substrate for Ga2O3 electronics. Copyright © 2025, The Authors. All rights reserved.

关键词： Computer resource management

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Data-driven sleep structure deciphering based on cardiorespiratory signals

引用

Computer Methods and Programs in Biomedicine 2025年 267卷 108769-108769页

作者： Huang, Ming Iwata, Osuke Yokoyama, Kiyoko Tamura, Toshiyo Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Shenzhen China of Science and Technology Nara Institute of Science and Technology Ikoma Japan of Medical Sciences Nagoya City University Japan School of Data Science Nagoya City University Japan Institute for Healthcare Robotics Waseda University Japan

Background and Objective: : Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) and low-frequency (LF) bands, indicating that signal segments of 4–8 min are optimal for analysis. However, the lack of labels tailored to these signals has led to reliance on the American Academy of Sleep Medicine (AASM) definitions, which are primarily designed for electroencephalogram (EEG) and electrooculogram (EOG) data. This study aims to address the challenge of transitioning from AASM-defined labels to cardiorespiratory-oriented ones and to evaluate the feasibility of using these signals for accurate sleep structure recognition. Methods: To align with the physiological characteristics of cardiorespiratory signals, AASM labels were modified by excluding the N2 stage due to its overlap of stable and unstable non-rapid eye movement (NREM) phases, which introduces ambiguity. The modified dataset focused on the wake, N1, deep sleep (N3), and rapid eye movement (REM) stages. A physiologically-inspired deep-learning model (PIDM) was developed to extract features from cardiorespiratory time series and classify sleep stages. Post-analysis assessed the physiological validity of the model's N2 predictions by evaluating the HF-to-LF ratio and respiratory variability. Results: The pipeline, combining the modified labeling scheme with the PIDM model, achieved balanced accuracy scores of 0.83, 0.86, and 0.78 for wake, deep sleep, and REM stages, respectively in the normal group;and 0.92, 0.95, and 0.90 in the mild and moderate sleep apnea groups. Post-analysis revealed that most N2 samples were attributed to stable NREM sleep, characterized by higher HF-to-LF ratios and lower respiratory variability, aligning with physiological understanding. Conclusions: This study highlights the physiological relevance of cardiorespiratory s

关键词： Electroencephalography

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Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding

arXiv

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arXiv 2025年

作者： Li, Jinze Xu, Yixing Huang, Haiduo Yin, Xuanwu Li, Dong Ngai, Edith C.H. Barsoum, Emad Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Advanced Micro Devices Inc. Beijing China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University China

Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multiple heads to predict a sequence of future tokens, where each head handles a token in the sequence. The target LLM verifies the predicted sequence and accepts aligned tokens, enabling efficient multi-token generation. However, existing methods assume that all tokens within a sequence are equally important, employing identical head structures and relying on a single-generation paradigm, either serial or parallel. To this end, we theoretically demonstrate that initial tokens in the draft sequence are more important than later ones. Building on this insight, we propose Gumiho, a hybrid model combining serial and parallel heads. Specifically, given the critical importance of early tokens, we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy. For later tokens, we utilize multiple lightweight MLP heads operating in parallel to enhance efficiency. By allocating more advanced model structures and longer running times to the early heads, Gumiho achieves improved overall performance. The experimental results demonstrate that our method outperforms existing approaches, fully validating its effectiveness. © 2025, CC BY.

关键词： Decoding

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Full State Quaternion-Based Observer Control for Multirotor Aerial Grasping

Full State Quaternion-Based Observer Control for Multirotor ...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： I. García-Mosqueda A. Tevera-Ruiz H. Abaunza P. Castillo A. Sanchez-Orta J.D. Chazot Universite de technologie de Compiegne CNRS Heudiasyc/Roberval Compiegne France Tecnologico de Monterrey School of Engineering and Sciences Jalisco Mexico CINVESTAV-Saltillo Robotics and Advanced Manufacturing Mexico

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents an enhanced observer control strategy for multirotor aerial grasping. Unlike previous approaches, which focused solely on translational dynamics, this method incorporates dual observers-one for the translational subsystem and another for the rotational dynamics. By lever-aging quaternions, the proposed control framework provides a singularity-free representation of orientation while naturally decoupling rotational and translational dynamics. This allows the system to be treated as fully actuated in both position and orientation, improving disturbance rejection and compensating for torques induced by offcenter or asymmetrically shaped objects during grasping. A passive, non-actuated gripper further enhances the drone's ability to interact with objects in real-world scenarios. Experimental validations confirm the robustness and adaptability of the proposed approach, demonstrating its effectiveness in handling dynamic variations in mass and torque while maintaining stable flight.

关键词： Torque Quaternions Grasping Observers Robustness Grippers Aircraft Aerospace control

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Formation Control of Unmanned Underwater Vehicles With Unknown Absolute Position Using Rigid Graph-Based MPC

引用

IEEE Internet of Things Journal 2025年

作者： Fu, Bowen Zhu, Daqi Chen, Mingzhi Yang, Simon X. University of Shanghai for Science and Technology Shanghai200093 China University of Guelph Advanced Robotics and Intelligent Systems Laboratory School of Engineering GuelphONN1G2W1 Canada

Formation control of unmanned underwater vehicles (UUVs) is of great significance to the Internet of Underwater Things (IoUT). Currently, various methods are employed for UUV formation control. Among them, rigid graph-based approaches, which rely solely on relative information between UUVs, are particularly suitable for underwater environments. However, traditional rigid graph-based formation control methods often face challenges such as control jumps and weak robustness in dynamic underwater environments. To address these challenges, a novel rigid graph-based model predictive controller (RGMPC) is proposed in this paper. The proposed approach integrates model predictive control with traditional rigid graph-based methods, effectively avoiding issues such as control jumps and thrust saturation while enhancing robustness. Moreover, constraints are constructed using backstepping methods to theoretically ensure the closed-loop stability of the algorithm. Finally, the algorithm is validated through extensive simulations based on mathematical models and further tested in the Gazebo simulator, fully demonstrating its feasibility and effectiveness. © 2014 IEEE.

关键词： Predictive control systems

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Developing a Framework for Natural Human Movement Mimicry of Low-Dynamic Motions in Mobile-Based Humanoids

Developing a Framework for Natural Human Movement Mimicry of...

引用

IEEE/SICE International Symposium on System Integration

作者： Simon Gormuzov Yushi Wang Pinchu Yang Tamon Miyake Tetsuya Ogata Shigeki Sugano Graduate School of Creative Science and Engineering Waseda University Tokyo Japan Future Robotics Organization Waseda University Tokyo Japan Faculty of Science and Engineering Waseda University Tokyo Japan The National Institute of Advanced Science and Technology Tokyo Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

In this work, we propose a framework that facilitates natural whole-body movements for a mobile-based humanoid. The framework takes bipedal human motion animation as input. After re-targeting the motion to the robot rig, the joint space data is applied to a physics-enabled robot model for balance confirmation and then deployed one-shot to the real robot. This method is beneficial for: 1) mapping expressive and low-dynamic whole-body motions, such as walking, to mobile-based robots; and 2) serving as a basis for training more complex control policies for more dynamic motions. Experiments were conducted by deploying human walking animations to the robot, assessing its ability to mirror the movements, and evaluating the subjective feelings of humans observing the robot performing the motions generated by both the proposed method and the traditional method. The results indicated that the proposed method is effective for mimicking human movements and consistently delivered a better overall impression in the natural appearance of the motion, the human-like factor, and friendliness.

关键词： Legged locomotion Training Dynamics Humanoid robots System integration Aerospace electronics Animation Data models Mirrors

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