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Dynamic Event-Triggered consensus control for Input constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

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IEEE/cAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin li Yue long Tieshan li Hongjing liang c.l.philip chen the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the laboratory of Electromagnetic Space cognition and Intelligent control Beijing 100089China the School of computer Science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

Adaptive neural network control of a 2-DOF helicopter system considering input constraints and global prescribed performance

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Science china(Information Sciences) 2024年第7期67卷 224-239页

作者： Zhijia ZHAO Jiale WU Zhijie lIU We HE c.l.philip chen School of Mechanical and Electrical Engineering Guangzhou University School of Intelligence Science and Technology and Key laboratory of Intelligent Bionic Unmanned Systems of Ministry of Education University of Science and Technology Beijing School of computer Science and Engineering South China University of Technology Pazhou lab

In this study, an adaptive neural network(NN) control is proposed for nonlinear two-degree-offreedom(2-DOF) helicopter systems considering the input constraints and global prescribed ***, radial basis function NN(RBFNN) is employed to estimate the unknown dynamics of the helicopter system. Second, a smooth nonaffine function is exploited to approximate and address nonlinear constraint functions. Subsequently, a new prescribed function is proposed, and an original constrained error is transformed into an equivalent unconstrained error using the error transformation and barrier function transformation methods. The analysis of the established lyapunov function proves that the controlled system is globally uniformly bounded. Finally, the simulation and experimental results on a constructed Quanser's test platform verify the rationality and feasibility of the proposed control.

关键词： adaptive NN control 2-DOF helicopter global prescribed performance input constraints

Boosting Adaptive Weighted Broad learning System for Multi-label learning

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IEEE/cAA Journal of Automatica Sinica 2024年第11期11卷 2204-2219页

作者： Yuanxin lin Zhiwen Yu Kaixiang Yang Ziwei Fan c.l.philip chen the School of computer Science and Engineering in South china University of Technology IEEE the Pengcheng laboratory

Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone to serious intra-class and inter-class imbalance problems, which can significantly degrade the classification performance. To address the above issues, we propose the multi-label weighted broad learning system(MlW-BlS) from the perspective of label imbalance weighting and label correlation mining. Further, we propose the multi-label adaptive weighted broad learning system(MlAW-BlS) to adaptively adjust the specific weights and values of labels of MlW-BlS and construct an efficient imbalanced classifier set. Extensive experiments are conducted on various datasets to evaluate the effectiveness of the proposed model, and the results demonstrate its superiority over other advanced approaches.

关键词： Broad learning system label correlation mining label imbalance weighting multi-label imbalance

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面向边缘计算应用的宽度孪生网络

自动化学报 2020年第10期46卷 2060-2071页

作者：李逸楷张通陈俊龙华南理工大学计算机科学与工程学院广州510006 琶洲实验室广州510355

边缘计算是将计算、存储、通信等任务分配到网络边缘的计算模式.它强调在用户终端附近执行数据处理过程,以达到降低延迟,减少能耗,保护用户隐私等目的.然而网络边缘的计算、存储、能源资源有限,这给边缘计算应用的推广带来了新的挑战.... 详细信息

边缘计算是将计算、存储、通信等任务分配到网络边缘的计算模式.它强调在用户终端附近执行数据处理过程,以达到降低延迟,减少能耗,保护用户隐私等目的.然而网络边缘的计算、存储、能源资源有限,这给边缘计算应用的推广带来了新的挑战.随着边缘智能的兴起,人们更希望将边缘计算应用与人工智能技术结合起来,为我们的生活带来更多的便利.许多人工智能方法,如传统的深度学习方法,需要消耗大量的计算、存储资源,并且伴随着巨大的时间开销.这不利于强调低延迟的边缘计算应用的推广.为了解决这个问题,我们提出将宽度学习系统(Broad learning system,BlS)等浅层网络方法应用到边缘计算应用领域,并且设计了一种宽度孪生网络算法.我们将宽度学习系统与孪生网络结合起来用于解决分类问题.实验结果表明我们的方法能够在取得与传统深度学习方法相似精度的情况下降低时间和资源开销,从而更好地提高边缘计算应用的性能.

关键词：宽度学习系统边缘计算孪生网络浅层网络边缘智能

基于多层注意力和消息传递网络的药物相互作用预测方法

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自动化学报 2023年第12期49卷 2507-2519页

作者：饶晓洁张通孟献兵陈俊龙华南理工大学计算机科学与工程学院广州510006 琶洲实验室广州510355

药物相互作用(Drug-drug interaction,DDI)是指不同药物存在抑制或促进等作用.现有DDI预测方法往往直接利用药物分子特征表示预测DDI,而忽略药物分子中不同原子对DDI的影响.为此,提出基于多层次注意力机制和消息传递神经网络的DDI预测方... 详细信息

药物相互作用(Drug-drug interaction,DDI)是指不同药物存在抑制或促进等作用.现有DDI预测方法往往直接利用药物分子特征表示预测DDI,而忽略药物分子中不同原子对DDI的影响.为此,提出基于多层次注意力机制和消息传递神经网络的DDI预测方法.该方法将DDI建模为通过学习基于序列表示的药物分子特征实现DDI预测的链接预测问题.首先,建立基于注意力机制和消息传递神经网络的原子特征网络,结合提出的基于分子质心的位置编码,学习不同原子及其相关联化学键的特征,构建基于图结构的药物分子特征表示;然后,设计基于注意力机制的分子特征网络,并通过监督和对比损失学习,实现DDI预测;最后,通过实验证明该方法的有效性和优越性.

关键词：药物相互作用预测多层次注意力机制消息传递神经网络位置编码

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基于图正则化的贝叶斯宽度学习系统

智能科学与技术学报 2022年第1期4卷 109-117页

作者：段俊伟许林灿全渝娟陈龙陈俊龙暨南大学信息科学技术学院广东广州510632 澳门大学科技学院中国澳门999078 华南理工大学计算机科学与工程学院广东广州510006

作为一种前馈神经网络,宽度学习系统因其精度高、训练速度快且能有效代替深度学习方法而备受研究者的关注。然而,宽度学习系统存在对网络中的特征节点个数比较敏感且求伪逆方式易使模型出现过拟合等问题。为此,在宽度学习系统中引入贝... 详细信息

作为一种前馈神经网络,宽度学习系统因其精度高、训练速度快且能有效代替深度学习方法而备受研究者的关注。然而,宽度学习系统存在对网络中的特征节点个数比较敏感且求伪逆方式易使模型出现过拟合等问题。为此,在宽度学习系统中引入贝叶斯推断和图正则化。一方面,通过引入先验知识进行贝叶斯学习可以有效提高权重的稀疏性,提高模型的稳定性;另一方面,加入图正则化可充分考虑数据内在的图信息,进一步提高模型的泛化能力。在UcI数据集和NORB数据集上对所提模型进行性能评估,实验结果表明,所提的基于图正则化的贝叶斯宽度学习系统模型能进一步提高宽度学习系统的分类精度且具有更好的稳定性。

关键词：宽度学习系统贝叶斯推断图正则化模式识别

Rogue wave solutions and rogue-breather solutions to the focusing nonlinear Schr?dinger equation

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communications in Theoretical Physics 2024年第3期76卷 33-41页

作者： Si-Jia chen Xing lü college of Science Tianjin University of TechnologyTianjin 300384People's Republic of China Department of Mathematics Beijing Jiaotong UniversityBeijing 100044People's Republic of China Beijing laboratory of National Economic Security Early-warning Engineering Beijing Jiaotong UniversityBeijing 100044People's Republic of China

Based on the long wave limit method,the general form of the second-order and third-order rogue wave solutions to the focusing nonlinear Schr?dinger equation are given by introducing some arbitrary *** interaction solutions between the first-order rogue wave and one-breather wave are constructed by taking a long wave limit on the two-breather *** applying the same method to the three-breather solutions,two types of interaction solutions are obtained,namely the first-order rogue wave and two breather waves,the second-order rogue wave and one-breather wave,*** influence of the parameters related to the phase on the interaction phenomena is graphically *** occur among the rogue waves and breather *** the collisions,the shape of them remains *** abundant interaction phenomena in this paper will contribute to a better understanding of the propagation and control of nonlinear waves.

关键词： nonlinear Schrodinger equation rogue wave solutions interaction solutions

Effects of layer interactions on instantaneous stability of finite Stokes flows

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Applied Mathematics and Mechanics(English Edition) 2024年第1期45卷 69-84页

作者： chen ZHAO Zhenli chen c.T.MUTASA Dong lI School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China

The stability analysis of a finite Stokes layer is of practical importance in flow control. In the present work, the instantaneous stability of a finite Stokes layer with layer interactions is studied via a linear stability analysis of the frozen phases of the base flow. The oscillations of two plates can have different velocity amplitudes, initial phases, and frequencies. The effects of the Stokes-layer interactions on the stability when two plates oscillate synchronously are analyzed. The growth rates of two most unstable modes when δ lmost equal, and δ = δ*/h*, where δ*and h*are the Stokes-layer thickness and the half height of the channel, respectively. However, their vorticities are different. The vorticity of the most unstable mode is symmetric, while the other is asymmetric. The Stokes-layer interactions have a destabilizing effect on the most unstable mode when δ lizing effect when δ > 0.68. However, the interactions always have a stabilizing effect on the other unstable mode. It is explained that one of the two unstable modes has much higher dissipation than the other one when the Stokes-layer interactions are strong. We also find that the stability of the Stokes layer is closely related to the inflectional points of the base-flow velocity profile. The effects of inconsistent velocity-amplitude, initial phase, and frequency of the oscillations on the stability are analyzed. The energy of the most unstable eigenvector is mainly distributed near the plate of higher velocity amplitude or higher oscillation frequency. The effects of the initial phase difference are complicated because the base-flow velocity is extremely sensitive to the initial phase.

关键词： finite Stokes layer instantaneous stability Stokes-layer interaction asynchronous oscillation

Performance analysis of fuzzy BlS using different cluster methods for classification

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Science china(Information Sciences) 2021年第4期64卷 232-234页

作者： Shuang FENG c.l.philip chen School of Applied Mathematics Beijing Normal University Faculty of Science and Technology University of Macau

Dear editor,Neural networks (NNs) and fuzzy systems are commonly used computational intelligence techniques, each with their own merits in terms of applications. The integration of NNs and fuzzy systems, which leads to a hybrid framework known as neuro-fuzzy systems, inherits the useful properties of its constituents:the learning power of an NN and the knowledge representation of a fuzzy inference system,

关键词： fuzzy broad learning system clustering fuzzy c-means classification TSK fuzzy system