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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Xu Jiayi Yu Jiaqi Wang Yixin Han Shijia School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Cross-domain object detection poses significant challenges due to the susceptibility of object detection models to data variance, particularly the domain shifts that can occur between different domains. To address the limitation, we draw inspiration from knowledge distillation, proposing a collaborative learning framework. Our method employs CycleGAN to generate target-style images, and during pretraining, an unsupervised domain adaptation teacher model is trained for each source-target pair. In the distillation process, our proposed algorithm implements an out-of-distribution estimation strategy to select samples that best align with the current model, thereby enhancing the cross-domain distillation process. Furthermore, each expert model is encouraged to collaborate by designating the student model as a bridge between different target domains, facilitated by the Exponential Moving Average (EMA) algorithm. Experiments show that the proposed method leverages structured information, not only does it perform well across various target domains, but it also yields favorable results compared to state-of-the-art unsupervised methods that are specifically trained on single source-target pair.

关键词： Bridges Adaptation models Federated learning Large language models Estimation Object detection Information processing Media Explosions Periodic structures

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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A GRU-based Automatic Weighting Factors Optimization Strategy for PMSM

A GRU-based Automatic Weighting Factors Optimization Strateg...

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Chinese Automation Congress (CAC)

作者： Jiaao Li Jie Jin Jianhua Zhang Zhuang Liu Xiaoning Shen School of Astronautics Harbin Institute of Technology Harbin China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The performance of model predictive control (MPC) in permanent magnet synchronous motor (PMSM) still remains a challenging problem due to the large torque ripple in lower speed. The cost function in conventional MPC generally use fixed weighting factors, which is not easy to adapt different operation scenario and keep balance between torque ripple suppression and current tracking accuracy. To address this issue, a gated recurrent units (GRU) network based weighting factors automated-regulation strategy is proposed for the MPC in PMSM. Through offline training, the weighting factors in MPC are tuned in real time and the current tracking accuracy as well as torque ripple in different conditions are ensured, which is superior to the conventional fixed weighting factors-based MPC. Finally, some simulation results verify the effectiveness of the proposed method.

关键词： Employee welfare Training Accuracy Simulation Predictive models Permanent magnet motors Real-time systems Table lookup Torque measurement Predictive control

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Adaptive Finite Time Prescribed Performance Fault Tolerant control for Spacecraft Attitude Maneuver

Adaptive Finite Time Prescribed Performance Fault Tolerant C...

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IEEE Conference on Decision and control

作者： Ze Yang Baoqing Yang Ruihang Ji Jie Ma Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Electrical and Computer Engineering National University of Singapore Singapore

In this paper, an active fault tolerant control method for spacecraft against actuator faults, uncertainties and disturbances is investigated. First, an adaptive iterative learning observer with improved adaptive law is proposed, which greatly improves the accuracy and speed of fault estimation. Then, a novel adaptive finite time prescribed performance fault tolerant controller is proposed, which has flexible performance constraints according to faults and control references, with better robustness and lower conservatism, breaking the limitation of fixed performance constraint. Next, an online optimal control allocation strategy is designed to achieve high-performance actuator allocation under saturation and fault constraints. Finally, through numerical simulation, the effectiveness and robustness of the proposed scheme are illustrated by comparing with existing methods.

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An emergent EV dispatching method to enhance the resilience of power-transportation coupling systems

An emergent EV dispatching method to enhance the resilience ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Jie Yang Xi Zhang Xingtang Wu School of Automation Beijing Institute of Technology Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

With the increasing deployment of electric vehicles, transportation networks have been more closely coupled with power networks via charging stations. The functionality of the coupled system can be significantly damaged by extreme events, like man-made attacks and natural disasters. In this paper, we propose a metric to quantify network resilience and a method to dispatch electric vehicles to suitable charging stations in power grid-coupled transportation networks after being disrupted by extreme events. The emergent dispatching problem is expressed by a linear programming model which is computationally tractable. The optimization variables are binary and represent the charging stations selected for electric vehicles. The optimization objective is to minimize the sum of queue time and travel time of electric vehicles. Simulation results conducted on a synthesized power-transportation coupling system that is composed by a modified real-world transportation network and the IEEE 39 Bus test case demonstrate the efficacy of the proposed method in enhancing network resilience. Our work contributes to the advancement of more resilient modern transportation networks under extreme events.

关键词： Couplings Simulation Transportation Charging stations Electric vehicles Dispatching Power grids

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Domain Adapted Object Detection with Intermediate Domain Generation

Domain Adapted Object Detection with Intermediate Domain Gen...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： He Yuhang Sun Yangyang Xue Zhijun Han Shijiao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Autonomous driving detection technology in real-world road scenarios faces numerous challenges, including variable weather conditions and complex road environments. Therefore, developing an object detection model with robust domain adaptation is crucial. In this paper, we investigate the use of image style transfer techniques to leverage target domain images for enhancing model performance. Experimental results show that our proposed approach significantly improves detection efficacy. Notably, our method outperforms the Oracle results in tasks such as transitioning from Cityscapes to Foggy Cityscapes, highlighting its effectiveness in addressing domain adaptation challenges.

关键词： Training Adaptation models Roads Object detection Information processing Detectors Media Autonomous vehicles Faces Meteorology

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Disturbances Observer-Based Fixed-Time Sliding Mode control for Three-Level NPC Converters in Microgrid

Disturbances Observer-Based Fixed-Time Sliding Mode Control ...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Guangxin Liu Xiaoning Shen Jianhua Zhang Yabin Gao Jianxing Liu School of Astronautics Harbin Institute of Technology Harbin China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

In this paper, a fixed-time disturbances observer (FTDOB)-based fixed-time sliding mode control (FTSMC) scheme is proposed for the three-phase three-level neutral-point-clamped (3L-NPC) converters. Therein, a FTSMC with adaptive exponential coefficient is designed to regulate the dc-link voltage. Compared with existing methods, the upper bound of the settling time for the proposed method is independent of the initial error, which ensures the dynamic performance of the 3L-NPC converters. Furthermore, a FTDOB is employed to estimate external disturbances and act as feedforward compensation of the 3L-NPC converters to enhance its disturbances rejection ability. Finally, a series of simulation results demonstrate the superiority of the proposed method by compared with several representative methods used in 3L-NPC converters.

关键词： Upper bound Simulation Microgrids Observers Voltage control Informatics Sliding mode control

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ELOFS: An Extensible Low-Overhead Flash File System for Resource-Scarce Embedded Devices

ELOFS: An Extensible Low-Overhead Flash File System for Reso...

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作者： Zhang, Runyu Liu, Duo Chen, Xianzhang She, Xiongxiong Yang, Chaoshu Tan, Yujuan Shen, Zhaoyan Shao, Zili Qiao, Lei Chongqing400044 China Chongqing University College of Computer Science Chongqing400044 China Shandong University School of Computer Science and Technology Qingdao266237 China The Chinese University of Hong Kong Department of Computer Science and Engineering NT 999077 Hong Kong Beijing Institute of Control Engineering Beijing100190 China

Emerging applications like machine learning in embedded devices (e.g., satellites and vehicles) require huge storage space, which recently stimulates the widespread deployment of large-scale flash memory in IoT devices. However, existing embedded file systems fall short in managing large-capacity storage efficiently for two reasons. First, prior arts store data structures of file systems either in flash or in main memory, which severely magnifies the scarcity of computing and memory resources. Moreover, the fine-grained metadata management in the existing embedded file systems induces significant energy consumption for large-capacity storage. In this paper, we propose a novel embedded file system, ELOFS, to tackle the above issues and manage large-capacity NAND flash on resource-scarce devices. ELOFS is made efficient through three novel techniques. First, we redefine the space management granularity and streamline the metadata to speed up the mounting performance. In addition, we design hybrid file structures to adapt dissimilar access patterns of embedded devices. Furthermore, ELOFS provides opportunities for in-depth cooperation with application-specific systems. We implement ELOFS with Memory Technology Device (MTD) interfaces, and the experimental results show that ELOFS outperforms YAFFS and UBIFS in terms of write, read, and deletions with orders of magnitude reductions on memory footprint and mounting time. © 1968-2012 IEEE.

关键词： Metadata

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Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems

arXiv

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arXiv 2023年

作者： Beintema, Gerben I. Schoukens, Maarten Toth, Roland Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

Available methods for identification of stochastic dynamical systems from input-output data generally impose restricting structural assumptions on either the noise structure in the data-generating system or the possible state probability distributions. In this paper, we introduce a novel identification method of such systems, which results in a dynamical model that is able to produce the time-varying output distribution accurately without taking restrictive assumptions on the data-generating process. The method is formulated by first deriving a novel and exact representation of a wide class of nonlinear stochastic systems in a so-called meta-state-space form, where the meta-state can be interpreted as a parameter vector of a state probability function space parameterization. As the resulting representation of the meta-state dynamics is deterministic, we can capture the stochastic system based on a deterministic model, which is highly attractive for identification. The meta-state-space representation often involves unknown and heavily nonlinear functions, hence, we propose an artificial neural network (ANN)-based identification method capable of efficiently learning nonlinear meta-state-space models. We demonstrate that the proposed identification method can obtain models with a log-likelihood close to the theoretical limit even for highly nonlinear, highly stochastic systems. © 2023, CC BY.

关键词： Stochastic systems

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On Improved Commutation for Moving-Magnet Planar Actuators

arXiv

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arXiv 2023年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary

The demand for high-precision and high-throughput motion control systems has increased significantly in recent years. The use of moving-magnet planar actuators (MMPAs) is gaining popularity due to their advantageous characteristics, such as complete environmental decoupling and reduction of stage mass. Nonetheless, model-based commutation techniques for MMPAs are compromised by misalignment between the mover and coil array and mismatch between the ideal electromagnetic model and the physical system, often leading to decreased system performance. To address this issue, a novel improved commutation approach is proposed in this paper, which is applicable for general planar motor applications, by means of dynamic regulation of the position dependence of the ideal model-based commutation algorithm, which allows for attenuation of magnetic misalignment, manufacturing inaccuracies and other unmodelled phenomena. The effectiveness of the proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator *** Codes 37M15 © 2023, CC BY.

关键词： Alignment

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