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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Yanmin Liu Xiaozhong Liao Zihao Wang Xi Chen Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

The unmanned aerial vehicles (UAVs) formation needs the frequent data-exchanging of individual's state between units for monitoring and instruction uploading from the ground station, which inevitably occupies huge communication bandwidth. This paper presents the extended Kalman filter (EKF) design based on the event-triggered strategy to get UAVs greatly relieved of the communication burden with guaranteed accuracy. The event-triggered strategy firstly selects only the state measurements containing innovational information for the purpose of filtering. Due to the nonlinearity of UAV system, the EKF is further applied to make full use of the information from the prior event-trigger strategy so as to enhance the performance of estimation. The proposed algorithm is verified on the physical UAVs regarding the estimation quality and communication rate, demonstrating the robust dynamic performance with effectively reduced communication rate.

关键词： Estimation Quaternions Unmanned aerial vehicles Monitoring Kalman filters Accelerometers Data models

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A Novel Multi-objective Evolutionary Algorithm Based on Space Partitioning 11th

A Novel Multi-objective Evolutionary Algorithm Based on Spac...

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11th International Symposium on Intelligence Computation and Applications, ISICA 2019

作者： Wu, Xiaofang Li, Changhe Zeng, Sanyou Yang, Shengxiang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9789811555763

To design an effective multi-objective optimization evolutionary algorithms (MOEA), we need to address the following issues: 1) the sensitivity to the shape of true Pareto front (PF) on decomposition-based MOEAs;2) the loss of diversity due to paying so much attention to the convergence on domination-based MOEAs;3) the curse of dimensionality for many-objective optimization problems on grid-based MOEAs. This paper proposes an MOEA based on space partitioning (MOEA-SP) to address the above issues. In MOEA-SP, subspaces, partitioned by a k-dimensional tree (kd-tree), are sorted according to a bi-indicator criterion defined in this paper. Subspace-oriented and Max-Min selection methods are introduced to increase selection pressure and maintain diversity, respectively. Experimental studies show that MOEA-SP outperforms several compared algorithms on a set of benchmarks. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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Temporal-Difference Spatial Sampling and Aggregating Graph Neural Network for Crowd Flow Forecasting

Temporal-Difference Spatial Sampling and Aggregating Graph N...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Xiaojie Bu Zebing Wei Zhishuai Li Xiao Wang Yuanyuan Chen Yunquan Song Yisheng Lv College of Science China University of Petroleum Qingdao China Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

With the development of traffic demand management, crowd flow forecasting arouse increasing interest. In order to tackle this spatial-temporal prediction problem, GNN (Graph Neural Networks) have been recently employed to model spatial dependencies, and usually spatial graphs are constructed based on geodetic distances or direct connections between nodes. However, it might be insufficient for spatial graphs to model real dependencies because they neglect spatial-temporal correlations. In this paper, a novel Temporal-Difference Spatial Sampling and Aggregating graph neural network (TDSSA) is proposed to model spatial-temporal dependencies. Firstly, a new sub-sparse spatial-temporal graph is constructed to represent spatial-temporal relationships among different nodes, then a TDSSA block is designed to extract features by spatial sampling and aggregating, and difference is utilized in TDSSA blocks to exploit temporal trend and increase robustness. Experiments show that the proposed method outperforms baseline methods.

关键词： Correlation Digital twin Conferences Aggregates Predictive models Feature extraction Market research

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Sequence impedance modeling of droop-controlled inverter 8

Sequence impedance modeling of droop-controlled inverter

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8th Renewable Power Generation Conference, RPG 2019

作者： Hu, You Wang, Jiajun Liu, Bin Li, Zhen Liu, Xiangdong School of Automation and Key Laboratory for Intelligent Control and Decision on Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781839531255

The grid-connected three-phase inverter is an indispensable part of the microgrid. The droop control is widely used in parallel inverters for high reliability and flexibility. The output impedance of droop controlled inverters plays an vital role in its stability. However, the sequence impedance model of grid-connected inverter is currently based on the grid side converter with a single current loop control exdluding the low-frequency dynamics similar in doubly fed induction generators. Both the droop control and voltage loop control greatly affect the stability of inverter, specifically in the low frequency response. This paper proposes a sequence impedance model of inverter, which considers the droop control and voltage and current dual closed-loop control using the harmonic linearization method in the frequency domain. The accuracy of the model is verified through comparing the measurement impedance value in simulation with the impedance value calculated in the sequence impedance model. The influence of control method on system impedance is verified by showing the difference between the single loop controlled inverter and droop control inverter. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Electric inverters

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S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Wang, Xiao Tang, Ke Dai, Xingyuan Xu, Jintao Du, Quancheng Ai, Rui Wang, Yuxiao Gu, Weihao Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei230031 China Haomo Technology Co. Ltd. Beijing100192 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266114 China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework. Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV’s planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S4TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs’ trajectories as input. With the integration of SADRF, S4TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S4TP in terms of safety and rationality. S4TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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A CNN-ELM Compound Fault Diagnosis Method Based on Joint Distribution Modification

A CNN-ELM Compound Fault Diagnosis Method Based on Joint Dis...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Jiechao Dong Liping Yan Yuanqing Xia Jinhui Zhang Xianghua Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Shandong Key Laboratory of Big-data Driven Safety Control Technology for Complex Systems Shandong China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based on joint distribution modification. Firstly, considering the complementarity and coupling of data from multiple sensors, a data input trick of multi-sensor data connected in parallel is designed. Secondly, due to the discrepancy of distribution between the compound fault data features and the single fault data features, the marginal distribution matrix and the posterior distribution matrix are used to modify the CNN-ELM network, so that the network can extract more reliable data features for fault diagnosis. Finally, referring to the categories and criteria of bearing damage proposed by Paderborn University, the label code is defined. The corresponding data set is used to verify the proposed algorithm. Experimental results show that the algorithm can accurately obtain detailed fault information such as fault location, fault type, and fault severity.

关键词： Fault diagnosis Rolling bearings Materials reliability Feature extraction Sensor systems Sensors Compounds

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A Unified Framework for Finite-/Fixed-Time Synchronization of Memristor Chaotic systems and Its Application in Image Encryption

Research Square

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Research Square 2021年

作者： Wang, Leimin Jiang, Shan Ge, Ming-Feng Hu, Junhao China University of Geosciences China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China College of Mathematics and Statistics South-Central University for Nationalities Wuhan430074 China

This paper proposes a sliding-mode-based unified control framework to solve the synchronization problem of memristor chaotic systems. Both finite- and fixed-time synchronization of the memristor chaotic systems can be obtained in the uniform framework. According to the Lyapunov stability and finite-time stability theories, we demonstrate that the trajectories of error system reach the presented sliding-mode surface and converge to the origin along the surface in a finite/fixed time. Moreover, an image encryption algorithm is developed based on the presented control framework. Finally, the numerical simulations and the statistical performance analyses are discussed to illustrate the correctness of synchronization results, the effectiveness of the proposed encryption algorithm, and its potential applications in the scope of secure communication. © 2021, CC BY.

关键词： Chaotic systems

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FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusion

arXiv

引用

arXiv 2023年

作者： Teng, Siyu Li, Luxi Li, Yuchen Hu, Xuemin Li, Lingxi Ai, Yunfeng Chen, Long Department of Computer Science Hong Kong Baptist University Hong Kong Department of Computer Science BNU-HKBU United International College Zhuhai China The School of Artificial Intelligence Hubei University Wuhan China Waytous Inc. Haidian Distinct Beijing China Indianapolis United States School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

In recent years, significant achievements have been made in motion planning for intelligent vehicles. However, as a typical unstructured environment, open-pit mining attracts limited attention due to its complex operational conditions and adverse environmental factors. A comprehensive paradigm for unmanned transportation in open-pit mines is proposed in this research. Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation. Then, we develop a novel benchmark called MiningNav, which offers three validation approaches to evaluate the trustworthiness and robustness of well-trained algorithms in transportation roads of open-pit mines. Finally, we introduce the Parallel Mining Simulator (PMS), a new high-fidelity simulator specifically designed for open-pit mining scenarios. PMS enables the users to manage and control open-pit mine transportation from both the single-truck control and multi-truck scheduling perspectives. The performance of FusionPlanner is tested by MiningNav in PMS, and the empirical results demonstrate a significant reduction in the number of collisions and takeovers of our planner. We anticipate our unmanned transportation paradigm will bring mining trucks one step closer to trustworthiness and robustness in continuous round-the-clock unmanned transportation. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Federated meta-learning for fraudulent credit card detection 29

Federated meta-learning for fraudulent credit card detection

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Zheng, Wenbo Yan, Lan Gou, Chao Wang, Fei-Yue School of Software Engineering Xi'an Jiaotong University China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China School of Intelligent Systems Engineering Sun Yat-sen University China School of Artificial Intelligence University of Chinese Academy of Sciences China

ISBN: (纸本)9780999241165

Credit card transaction fraud costs billions of dollars to card issuers every year. Besides, the credit card transaction dataset is very skewed, there are much fewer samples of frauds than legitimate transactions. Due to the data security and privacy, different banks are usually not allowed to share their transaction datasets. These problems make traditional model difficult to learn the patterns of frauds and also difficult to detect them. In this paper, we introduce a novel framework termed as Federated Meta-Learning for fraud detection. Different from the traditional technologies trained with data centralized in the cloud, our model enables banks to learn fraud detection model with the training data distributed on their own local database. A shared whole model is constructed by aggregating locally-computed updates of fraud detection model. Banks can collectively reap the benefits of shared model without sharing the dataset and protect the sensitive information of cardholders. To achieve the good performance of classification, we further formulate an improved triplet-like metric learning, and design a novel meta-learning-based classifier, which allows joint comparison with K negative samples in each mini-batch. Experimental results demonstrate that the proposed approach achieves significantly higher performance compared with the other state-of-the-art approaches. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Crime

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A threshold segmentation method for non-uniform illumination image based on brightness equalization 2

A threshold segmentation method for non-uniform illumination...

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2019 2nd International Conference on advanced Materials, intelligent Manufacturing and automation, AMIMA 2019

作者： Guo, Hui Chen, Peng Huang, Shun Hu, Cong Zhang, Lijun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China

In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation. © Published under licence by IOP Publishing Ltd.

关键词： Luminance

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