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On PID control for synchronization of complex dynamical network with delayed nodes

Science China(Technological Sciences) 2019年第8期62卷 1412-1422页

作者： GU HaiBo Lv JinHu LIN ZongLi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University Beijing 100083 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

Over the past two decades, synchronization, as an interesting collective behavior of complex dynamical networks, has been attracting much attention. To reveal and analyze the inherent mechanism of synchronization in complex dynamical networks with time delays in nodes, this paper attempts to use PD and PI control protocols to achieve synchronization. Based on a classical network model, we investigate the PD and PI control for synchronization of complex dynamical networks with delayed nodes and obtain some sufficient conditions. By using Lyapunov functions and appropriate state transformations, we prove that global synchronization can be achieved via the above control protocols. Finally, some simulation examples are illustrated to validate the effectiveness of the proposed theoretical results.

关键词： synchronization PID control complex dynamical network networked control system delayed node

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Learning Network-Invariant and Label-Discriminative Representations for Cross-Network Node Classification

Learning Network-Invariant and Label-Discriminative Represen...

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Chinese Automation Congress (CAC)

作者： Linyao Yang Yancai Xu Jiachen Hou Yuxin Dai Chen Lv The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Institute of Systems Engineering Macau University of Science and Technology Macau China School of Electrical Engineering and Automation Wuhan University Wuhan China China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665426480

Networks are ubiquitous data structures in the real world. The accurate and efficient analysis of networks is critical to realizing many intelligent network-based services. However, most existing network analysis methods are developed for single networks and require a lot of labeled data, which is costly and time-consuming to acquire. Transfer learning has been widely accepted as an effective paradigm for tackling this problem by reusing the model trained on a supervised task. However, transfer learning on the non-euclidean network data has been investigated by no more than a few studies. To realize accurate node classification based on the knowledge learned from the labeled source network, this paper proposes to learn network-invariant and label-discriminative representations based on graph embedding and linear discriminant analysis. Specifically, we embed the source and target networks into adjacent vector spaces based on the graph attention network by minimizing the Sinkhorn distributional distances between their embeddings. To obtain label-discriminative features for learning better classification models, we then utilize a transferable linear discriminative analysis method to project the embeddings into label-discriminative subspaces. In the end, a support vector machine model trained on the labeled source network is utilized to classify the target nodes. Experiments on two pairs of networks illustrate that our method achieves the best performance and evaluates the effectiveness of the proposed modules.

关键词： Support vector machines Knowledge engineering Analytical models Automation Transfer learning Network analyzers Data structures

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Identification of switched linear systems: Persistence of excitation and numerical algorithms

arXiv

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arXiv 2021年

作者： Mu, Biqiang Chen, Tianshi Cheng, Changming Bai, Er-Wei Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Iowa Iowa CityIA52242 United States

This paper investigates two issues on identification of switched linear systems: persistence of excitation and numerical algorithms. The main contribution is a much weaker condition on the regressor to be persistently exciting that guarantees the uniqueness of the parameter sets and also provides new insights in understanding the relation among different subsystems. It is found that for uniquely determining the parameters of switched linear systems, the minimum number of samples needed derived from our condition is much smaller than that reported in the literature. The secondary contribution of the paper concerns the numerical algorithm. Though the algorithm is not new, we show that our surrogate problem, relaxed from an integer optimization to a continuous minimization, has exactly the same solution as the original integer optimization, which is effectively solved by a block-coordinate descent algorithm. Moreover, an algorithm for handling unknown number of subsystems is proposed. Several numerical examples are illustrated to support theoretical analysis. Copyright © 2021, The Authors. All rights reserved.

关键词： Integer programming

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Pinning boundary sampled-data synchronization of coupled reaction–diffusion neural networks

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Neurocomputing 2025年 648卷

作者： Zi-Peng Wang Bo-Ming Chen Junfei Qiao Biao Luo Huai-Ning Wu Tingwen Huang Guangwei Chen School of Information Science and Technology Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System and Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing 100124 China School of Automation Central South University Changsha 410083 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen 518107 China

In this paper, the pinning boundary sampled-data (SD) synchronization problem of coupled reaction–diffusion neural networks (CRDNNs) with SD-based couplings is investigated under boundary and distributed SD measurements. First, a pinning boundary SD controller is designed to effectively address the synchronization problem of CRDNNs, utilizing boundary and distributed SD measurements and requiring only a small number of sensors and actuators. Then, linear matrix inequalities provide adequate conditions that ensure exponential stability of the synchronization error system by using the designed pinning boundary SD controller, derived through inequality techniques and Lyapunov functionals. Finally, we present a numerical example to showcase the practical applicability and effectiveness of the proposed pinning boundary SD synchronization method.

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Energy-Efficient Cell-Free Massive MIMO Through Sparse Large-Scale Fading Processing

arXiv

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arXiv 2022年

作者： Chen, Shuaifei Zhang, Jiayi Björnson, Emil Demir, Özlem Tuğfe Ai, Bo The School of Electronic and Information Engineering The Frontiers Science Center for Smart Highspeed Railway System Beijing Jiaotong University Beijing100044 China Purple Mountain Laboratories Nanjing211111 China The Department of Computer Science KTH Royal Institute of Technology Kista164 40 Sweden The Department of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Turkey The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China

Cell-free massive multiple-input multiple-output (CF mMIMO) systems serve the user equipments (UEs) by geographically distributed access points (APs) by means of joint transmission and reception. To limit the power consumption due to fronthaul signaling and processing, each UE should only be served by a subset of the APs, but it is hard to identify that subset. Previous works have tackled this combinatorial problem heuristically. In this paper, we propose a sparse distributed processing design for CF mMIMO, where the AP-UE association and long-term signal processing coefficients are jointly optimized. We formulate two sparsity-inducing mean-squared error (MSE) minimization problems and solve them by using efficient proximal approaches with block-coordinate descent. For the downlink, more specifically, we develop a virtually optimized large-scale fading precoding (V-LSFP) scheme using uplink-downlink duality. The numerical results show that the proposed sparse processing schemes work well in both uplink and downlink. In particular, they achieve almost the same spectral efficiency as if all APs would serve all UEs, while the energy efficiency is 2-4 times higher thanks to the reduced processing and signaling. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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Dielectric Spectrum of Random Copolymerization Polypropylene Nanocomposites Doped with Nano Silica at Different Temperatures

Dielectric Spectrum of Random Copolymerization Polypropylene...

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International Conference on High Voltage engineering and Application, ICHVE

作者： Rujia Men Zhipeng Lei Jiancheng Song Kunying Han Lu Li Chuangyang Li Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT USA

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Random copolymerization polypropylene (PPR), a recyclable thermoplastic material with a melting temperature of over 150°C and excellent mechanical properties, has potential to become the insulation materials used in high voltage cables. To investigate dielectric properties of PPR and its nanocomposites at different temperatures, especially the dielectric spectrum at high temperatures, film samples of PPR and its nanocomposites doped with different content of nano silica were prepared. The microscopic morphologies were observed firstly for analyzing the dispersion of nanoparticles. Then the dielectric spectrums were measured at temperatures of 30, 50, 70, 90, 110 and 130°C. After this, the effects of nanoparticle content, temperature and frequency on the relative permittivity and dielectric dissipation factors are discussed and the mechanism is analyzed. It can be concluded that relative permittivity of PPR and its nanocomposites are almost unaffected by temperature in the range of 30 - 110°C and remains relatively low values. When the temperature is below 110°C, the relative permittivity of the PPR nanocomposites increases with the increase of temperature; And when the temperature is 110°C or above, the value is related to the applied voltage frequency and the content of nanoparticles. And with the temperature rising, the dielectric dissipation factor of PPR nanocomposites have an evident increase at lower frequency, which contributes to the DC conductivity.

关键词： Temperature Nanocomposites Permittivity Dielectrics Temperature measurement Nanoparticles Time-frequency analysis

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Selecting of global phenological field observations for validating coarse AVHRR-derived forest phenology products based on spatial heterogeneity and temporal consistency

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Ecological Informatics 2025年 90卷

作者： Shao, Qi Huang, Chao Xiao, Yuanjun Liu, Li Liu, Weiwei Huang, Ran Zhou, Chang Weng, Wei Huang, Jingfeng Key Laboratory of Environmental Remediation and Ecological Health Ministry of Education Zhejiang University Hangzhou 310058 China State Key Laboratory of Soil Pollution Control and Safety Zhejiang University Hangzhou 310058 China Institute of Applied Remote Sensing and Information Technology Zhejiang University Hangzhou 310058 China Key Laboratory of Agricultural Remote Sensing and Information Systems Hangzhou 310058 China Key Laboratory of National Forestry and Grassland Administration on Forest Ecosystem Protection and Restoration of Poyang Lake Watershed College of Forestry Jiangxi Agricultural University Nanchang 330045 China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering College of Computer and Information Technology China Three Gorges University Yichang 443002 China Department of Geography and Spatial Information Techniques Ningbo University Ningbo 315211 China School of Automation Hangzhou Dianzi University Xiasha Higher Education Zone Hangzhou 310058 China

Global phenological field observations play a crucial role in validating remote sensing products and algorithms. However, due to the spatial mismatch and scale effect between the field observations and the pixels of remote sensing phenology products, a direct comparison often leads to scale errors and increased uncertainty. Therefore, evaluating the spatial representativeness of field observations for remote sensing product validation is essential. This study developed a novel “bottom-up” evaluation framework named MSPT (Main land cover type, Spatial heterogeneity, Point-area consistency and Temporal consistency), which comprehensively assesses the spatial representativeness of forest phenological field observations within the coarse spatial scale. Based on MSPT method, the capability of global forest phenological field observations to support coarse-scale remote sensing validation was evaluated. Compared with the general method, MSPT significantly improved validation performance. For the start of the growing season (SOS), the root mean square error (RMSE) decreased from 49.70 to 33.75 days, and the percent bias (PBIAS) changed from −0.14 to 0.03. For the end of the growing season (EOS), the RMSE was reduced from 83.42 to 42.53 days, and the PBIAS decreased from 0.15 to 0.08. These findings demonstrate that MSPT enhances the reliability of validation datasets and effectively reducing uncertainty in the evaluation of coarse AVHRR-derived forest phenology products. The framework offers new insights into resolving the scale mismatch between field observations and the pixels of remote sensing products. © 2025

关键词： Field observations Forest phenology Satellite product Spatial mismatch Spatial representativeness

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Dielectric Strength of Ethylene Propylene Rubber under Thermal and Mechanical Stress

Dielectric Strength of Ethylene Propylene Rubber under Therm...

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International Conference on High Voltage engineering and Application, ICHVE

作者： Yang Liu Rujia Men Muqin Tian Ye Wang Kunying Han Zhipeng Lei Chuangyang Li Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT USA

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

In order to find out the effect of temperature and mechanical stress on the dielectric breakdown strength of Ethylene Propylene Rubber (EPR), AC breakdown tests of EPR samples were carried out at different temperatures and compressive stress. Two-parameter Weibull statistical distribution was used to analyze the breakdown strength. The experimental results show that the dielectric strength of EPR decreases with the increase of temperature when only temperature is applied. Under the same temperature, the breakdown strength of EPR firstly increases with the compressive stress rising, gradually reaches a maximum and finally shows a decreasing tendency. It's due to the effect of compressive stress on the intermolecular distance and thermal expansion of EPR.

关键词： Electric breakdown Stress Compressive stress Insulation Dielectric breakdown Bars Electric fields

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A differential-cascaded paradigm for control of nonlinear systems

arXiv

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arXiv 2020年

作者： Wang, Hanlei Ren, Wei Cheah, Chien Chern Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Department of Electrical and Computer Engineering University of California at Riverside RiversideCA92521 United States School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore

This paper focuses on developing a new paradigm motivated by investigating the consensus problem of networked Lagrangian systems with time-varying delay and switching topologies. We present adaptive controllers with piecewise continuous or arbitrary times differentiable control torques for realizing consensus of Lagrangian systems, extending the results in the literature. This specific study motivates the formulation of a new paradigm referred to as forwardstepping, which is shown to be a systematic tool for solving various nonlinear control problems. One distinctive point associated with forwardstepping is that the order of the reference dynamics is typically specified to be equal to or higher than that of the original nonlinear system, and the reference dynamics and the nonlinear system are governed by a differential/dynamic-cascaded structure. The order invariance or increment of the specified reference dynamics with respect to the nonlinear system and their differential/dynamic-cascaded structure expands significantly the design freedom and thus facilitates the seeking of solutions to many nonlinear control problems which would otherwise often be intractable. Copyright © 2020, The Authors. All rights reserved.

关键词： Lagrange multipliers

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An Adaptive Federated control Strategy for Participant Selection in Multi-Client Collaboration

An Adaptive Federated Control Strategy for Participant Selec...

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

作者： Yizhu Chen Xiaoming Du Xiao Wang Jun Jason Zhang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Electrical Engineering and Automation Wuhan University Wuhan China

The federated ecology provides a new paradigm for breaking the isolated data island problem and fully activating the potential of big data and artificial intelligence, especially in multi-client collaboration tasks. Participant selection strategy in multi-client collaboration is the main limitation for increasing the convergence speed and lowing the communication costs. However, in the face of the unbalanced and non-IID data distributions, the performance of federated optimization algorithms will also decrease. To solve the above problems, we propose an adaptive federated control strategy for participant selection in multi-client collaboration based on the Mann-Kendall test, named FedMK. By adaptively selecting weak participants for training rather than random selection, FedMK can speed up model convergence and reduce communication costs. Experiment results show that our method outperforms the baseline method in non-IID scenarios, and the number of communication rounds on CIFAR-10 and synthetic datasets reduced by more than 15% and 10 %,9 respectively.

关键词： Training Adaptation models Costs Biological system modeling Collaboration Optimization methods Ecology

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