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arXiv 2019年

作者： Feng, Guoliang Lu, Wei Pedrycz, Witold Yang, Jianhua Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116023 China School of Automation Engineering Northeast Electric Power University Jilin132012 China School of Control Science and Engineering Dalian University of Technology Dalian116023 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dynamic systems. However, these methods are faced with several obvious limitations. Most of these models are extremely time consuming when learning the large-scale FCMs with hundreds of nodes. Furthermore, the FCMs learned by those algorithms lack robustness when the experimental data contain noise. In addition, reasonable distribution of the weights is rarely considered in these algorithms, which could result in the reduction of the performance of the resulting FCM. In this article, a straightforward, rapid, and robust learning method is proposed to learn FCMs from noisy data, especially, to learn large-scale FCMs. The crux of the proposed algorithm is to equivalently transform the learning problem of FCMs to a classic-constrained convex optimization problem in which the least-squares term ensures the robustness of the well-learned FCM and the maximum entropy term regularizes the distribution of the weights of the well-learned FCM. A series of experiments covering two frequently used activation functions (the sigmoid and hyperbolic tangent functions) are performed on both synthetic datasets with noise and real-world datasets. The experimental results show that the proposed method is rapid and robust against data containing noise and that the well-learned weights have better distribution. In addition, the FCMs learned by the proposed method also exhibit superior performance in comparison with the existing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Fuzzy rules

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Multi-objecive LPV control of wind energy conversion system under wide-scale operating conditions 8

Multi-objecive LPV control of wind energy conversion system ...

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8th Renewable Power Generation Conference, RPG 2019

作者： Qu, Chenzhi Lin, Zhongwei Xie, Zhen Li, Yilin Zhang, Shangang Li, Xiongwei Duan, Zhenqing State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China New Energy Co. Ltd Jinan250099 China Guodian New Energy Technology Research Institute Co. Ltd Beijing102209 China

ISBN: (纸本)9781839531255

Wind energy conversion system (WECS) is essentially a time-varying system with high nonlinear characteristics, which leads to the difficulty of guaranteeing the control performance in a wide-scale operating conditions for the conventional linear control strategies. In this paper, a linear-parameter-varying (LPV) gain-scheduled controller is proposed for variable-speed-variable-pitch wind turbines above rated wind speed, which improves both steady- and dynamic-response performances under wide-scale operating conditions. Firstly, the H2/H∞ technique is adopted to reduce the rated power tracking errors, while enhancing the robustness against high-frequency turbulence. Secondly, the regional pole placement technique is applied on WECS, which builds the connections to the dynamic response performance. To verify the effectiveness of the proposed method, the simulation is implemented on the NREL 5 MW wind turbine, which is compared with the conventional local linear control strategy with a full analysis on the related performances. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Wind power

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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Predictive generalized graph fourier transform for attribute compression of dynamic point clouds

arXiv

引用

arXiv 2019年

作者： Xu, Yiqun Wang, Shanshe Zhang, Xinfeng Wang, Shiqi Ma, Siwei Guo, Zongming Gao, Wen Institute of Computing Technology University of Chinese Academy of Sciences National Engineering Laboratory for Video Technology Peking University Institute of Computer Science and Technology Peking University National Engineering Laboratory for Video Technology Peking University School of Computer and Control Engineering University of the Chinese Academy of Sciences Department of Computer Science City University of Hong Kong

As 3D scanning devices and depth sensors advance, dynamic point clouds have attracted increasing attention as a format for 3D objects in motion, with applications in various fields such as tele-presence, navigation for autonomous driving and heritage reconstruction. Nevertheless, the tremendous amount of data in dynamic point clouds significantly burden transmission and storage. We thus propose a complete compression framework for attributes of 3D dynamic point clouds, focusing on optimal inter-coding. Firstly, we derive the optimal inter-prediction and predictive transform coding assuming the Gaussian Markov Random Field model for attributes of dynamic point clouds, where the optimal predictive transform proves to be the Generalized Graph Fourier Transform (GGFT). Secondly, we propose refined motion estimation via efficient registration prior to inter-prediction, which searches the temporal correspondence between adjacent frames of point clouds. Finally, we construct a complete framework based on the optimal inter-coding and our previously proposed intra-coding, where we determine the optimal coding mode from rate-distortion optimization with the proposed offline-trained λ-Q model. Experimental results show that we achieve 13:4% bitrate reduction on average and up to 25:8% over the state-of-the-art Region-adaptive Hierarchical Transform method. Copyright © 2019, The Authors. All rights reserved.

关键词： Motion estimation

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An Adaptive Strategy via Reinforcement Learning for the Prisoner＇s Dilemma Game

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 301-310页

作者： Lei Xue Changyin Sun Donald Wunsch Yingjiang Zhou Fang Yu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing 210096 China Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA College of Automation Nanjing University of Posts and Telecommunications Nanjing 210023 China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai 210096 China IEEE

The iterated prisoner's dilemma(IPD) is an ideal model for analyzing interactions between agents in complex networks. It has attracted wide interest in the development of novel strategies since the success of tit-for-tat in Axelrod's tournament. This paper studies a new adaptive strategy of IPD in different complex networks, where agents can learn and adapt their strategies through reinforcement learning method. A temporal difference learning method is applied for designing the adaptive strategy to optimize the decision making process of the agents. Previous studies indicated that mutual cooperation is hard to emerge in the IPD. Therefore, three examples which based on square lattice network and scale-free network are provided to show two features of the adaptive strategy. First, the mutual cooperation can be achieved by the group with adaptive agents under scale-free network, and once evolution has converged mutual cooperation, it is unlikely to shift. Secondly, the adaptive strategy can earn a better payoff compared with other strategies in the square network. The analytical properties are discussed for verifying evolutionary stability of the adaptive strategy.

关键词： Complex network prisoner’s dilemma reinforcement learning temporal differences learning

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Multi-objective optimization of wind turbine via controllers coordination and sensitivity analysis 8

Multi-objective optimization of wind turbine via controllers...

引用

8th Renewable Power Generation Conference, RPG 2019

作者： Chen, Zhenyu Lin, Zhongwei Wang, Chuanxi Han, Xiangyu Li, Gengda Hu, Feng Si, Zongming State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China Guodian New Energy Technology Research Institute Co. Ltd Beijing102209 China New Energy Co. Ltd Jinan250099 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

In this paper, a sensitivity-analysis-based wind turbine optimization strategy is introduced to improve the power output stability while reducing the shaft and tower loads. Both generator torque and blade pitch are controlled coordinately to achieve the optimization. During the wind turbine control process, blade pitch and generator torque are controlled proportionally to the generator speed tracking error, which simplifies the controller structure, thus, the wind turbine performance can be evaluated with control variables sensitivities directly. The wind turbine performance is considered in output power stability, shaft bending moment and tower bending moment. Both load parameters are analysed in fatigue damage lifetime. A conflicting relationship is realized between the load-power characteristic during the optimization, and a global coordination solution is selected on the pareto optimal frontier. Essential, this work is an exploration for the quantitative analysis from the wind turbine load performance to the control variables sensitivities directly without the limitation of controller forms. Simulation results show the effectiveness of the proposed controller. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Multiobjective optimization

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PID2018 Benchmark Challenge: Model-based Feedforward Compensator with A Conditional Integrator

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IFAC-PapersOnLine 2018年第4期51卷 888-893页

作者： Yuan, Jie Ates, Abdullah Dehghan, Sina Zhao, Yang Fei, Shumin Chen, YangQuan School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey Mechatronics Embedded Systems and Automation Lab University of California MercedCA95340 United States School of Science and Engineering Shandong University Jinan250061 China Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing210096 China

Since proportional-integral-derivative (PID) controllers absolutely dominate the control engineering, numbers of different control structures and theories have been developed to enhance the efficiency of PID controllers. Thus, it is essential and inspiring to operate different PID control strategies to the PID2018 Benchmark Challenge. In this paper, a novel control strategy is designed for this refrigeration system, where a feedforward compensator and a conditional integrator are utilized to compensate the disturbances and remove the steady-state error in the benchmark problem, respectively. The simulation results given in the benchmark problem show the straightforward effectiveness of the proposed control structure compared with the existing control methods. © 2018

关键词： controllers Benchmarking Disturbance rejection Electric control equipment Proportional control systems Refrigeration Three term control systems Two term control systems Conditional integrators Feed forward compensation Model based method PID controllers Refrigeration system

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Nonlinear Modeling of the Subcritical Boiler-turbine System with Stochastic Differential Equations∗

Nonlinear Modeling of the Subcritical Boiler-turbine System ...

引用

2019 IEEE International Conference on Power Data Science, ICPDS 2019

作者： Du, Ming Xia, Jie Qian, Yonggui Li, Xiaobin Cai, Guoyuan Liu, Rui School of Control and Computer Engineering North China Electric Power University Beijing China Huaihu Coal and Electricity Co. Ltd. Tianji Power Plant Huainan Anhui Province232000 China China Railway Beijing Bureau Group Co. Ltd. Beijing West Power Section Official Beijing China

ISBN: (纸本)9781728137759

With the large-scale renewable energy integrated into power system, the optimization of coordinated control system (CCS) is increasingly crucial. The dynamics of subcritical boiler-turbine system have been studied through kinds of modeling methods. But the ordinary differential equations (ODEs) are used in previous studies mainly, which can not reflect the uncertainties in this system. In this work, the uncertainties in subcritical boiler-turbine system had been analyzed and the dynamics had been described with stochastic differential equations (SDEs). Great improvements of boiler- turbine system model can be seen in the simulations. This model can be the platform to study stochastic model predictive control in CCS. © 2019 IEEE.

关键词： Ordinary differential equations

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Eddy Current Method in Non-Magnetic Aluminide Coating Thickness Assessment

引用

Journal of Nondestructive Evaluation 2025年第3期44卷

作者： Tytko, Grzegorz Adamczyk-Habrajska, Malgorzata Li, Yong Pengpeng, Shi Kopec, Mateusz Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland Faculty of Science and Technology University of Silesia Chorzów41-500 Poland State Key Laboratory for Strength and Vibration of Mechanical Structures Shaanxi Engineering Research Centre of NDT and Structural Integrity Evaluation Xi’an Jiaotong University Shaanxi Xi’an China School of Mathematics and Statistics Ningxia University Ningxia Yinchuan750021 China Institute of Fundamental Technological Research Polish Academy of Sciences Pawińskiego 5B Warsaw02-106 Poland

This study investigates the use of eddy current testing (ECT) as a non-destructive technique to evaluate the thickness and structural variations of non-magnetic aluminide coatings on MAR-M247 nickel-based superalloy. Coatings with thicknesses of 20 μm and 40 μm were applied to substrates exhibiting fine, coarse, and columnar grain structures. Using sensors of different geometries, impedance measurements were performed within a frequency range of 11.5 MHz to 12.5 MHz. Results demonstrated the designed sensor’s superior sensitivity, with the highest values of absolute resistance difference significantly exceeding the threshold for reliable distinction due to coating thicknesses or grain structures. The study highlights the impact of eddy current penetration depth and edge effects on the measurement accuracy, emphasizing the need for optimized sensor design and frequency selection. Findings confirm the efficacy of ECT in differentiating coatings of varying thicknesses and substrate structures, offering a reliable tool for quality control in high-temperature applications. © The Author(s) 2025.

关键词： Eddy current testing

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Evaluating Local Geometric Feature Representations for 3D Rigid Data Matching

arXiv

引用

arXiv 2019年

作者： Yang, Jiaqi Quan, Siwen Wang, Peng Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Poly-technical University Xi’an710129 China School of Electronic and Control Engineering Chang’An University Xi’an710064 China

—Local geometric descriptors remain an essential component for 3D rigid data matching and fusion. The devise of a rotational invariant local geometric descriptor usually consists of two steps: local reference frame (LRF) construction and feature representation. Existing evaluation efforts have mainly been paid on the LRF or the overall descriptor, yet the quantitative comparison of feature representations remains unexplored. This paper fills this gap by comprehensively evaluating nine state-of-the-art local geometric feature representations. Our evaluation is on the ground that ground-truth LRFs are leveraged such that the ranking of tested feature representations are more convincing as opposed to existing studies. The experiments are deployed on six standard datasets with various application scenarios (shape retrieval, point cloud registration, and object recognition) and data modalities (LiDAR, Kinect, and Space Time) as well as perturbations including Gaussian noise, shot noise, data decimation, clutter, occlusion, and limited overlap. The evaluated terms cover the major concerns for a feature representation, e.g., distinctiveness, robustness, compactness, and efficiency. The outcomes present interesting findings that may shed new light on this community and provide complementary perspectives to existing evaluations on the topic of local geometric feature description. A summary of evaluated methods regarding their peculiarities is also presented to guide real-world applications and new descriptor crafting. Copyright © 2019, The Authors. All rights reserved.

关键词： Shot noise

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