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Identification of fractional order Hammerstein models based on mixed signals

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Journal of control and Decision 2024年第1期11卷 132-138页

作者： Mengqi Sun Hongwei Wang Qian Zhang school of control Science and engineering Dalian University of TechnologyDalianPeople’s Republic of China school of Electrical engineering Xinjiang UniversityUrumqiPeople’s Republic of China

An algorithm based on mixed signals is proposed,to solve the issues of low accuracy of identification algorithm,immeasurable intermediate variables of fractional order Hammerstein model,and how to determine the magnitude of fractional order.In this paper,a special mixed input signal is designed to separate the nonlinear and linear parts of the fractional order Hammerstein model so that each part can be identified independently.The nonlinear part is fitted by the neural fuzzy network model,which avoids the limitation of polynomial fitting and broadens the application range of nonlinear models.In addition,the multi-innovation Levenberg-Marquardt(MILM)algorithm and auxiliary recursive least square algorithm are innovatively integrated into the parameter identification algorithm of the fractional order Hammerstein model to obtain more accurate identification results.A simulation example is given to verify the accuracy and effectiveness of the proposed method.

关键词： Mixed signal fractional order Hammerstein model neural fuzzy network model multi-innovation Levenberg-Marquardt algorithm

Research on Credit Regulation Mechanism of E-commerce Platform Based on Evolutionary Game Theory

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Journal of Systems Science and Systems engineering 2024年第3期33卷 330-359页

作者： Zeguo Qiu Yuchen Yin Yao Yuan Yunhao Chen school of computer and Information engineering Harbin University of CommerceHarbin150028China school of Management Harbin University of CommerceHarbin150028China

In the growing e-commerce industry,the problem of malicious business operations has become increasingly prominent,exposing many problems such as weak supervision of e-commerce platforms and no way for consumers to complain.In order to solve the problems of counterfeit and shoddy products on e-commerce platforms and promote the sustainable development of the e-commerce industry in China,this paper constructs a three-party evolutionary game model of e-commerce platforms,merchants,and consumers,investigates the influence of each influencing factor on each party’s strategy choice,and provides targeted suggestions to e-commerce platforms based on relevant factors.Finally,the impact of several important parameters on the equilibrium solution is discussed through sensitivity analysis.The results show that:1)the smaller the cost difference between active and negative regulation,the more the e-commerce platform tends to active regulation strategy,but increasing fines for dishonest merchants and consumer complaints have little impact on the e-commerce platform;2)increasing consumer compensation,creating an honest business environment,and reducing the cost of honest business all help companies tend to operate in good faith;3)the only factor that affects the tendency of consumer complaint strategies is the cost of complaints.The loss suffered by silence and the compensation given to consumers have little effect on consumers’tendency to complain strategy.The results can provide theoretical guidance for participants to make useful strategic decisions in the e-commerce market.

关键词： Evolutionary game e-commerce data simulation

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

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computers, Materials & Continua 2024年第1期78卷 1095-1113页

作者： Fang Xu Songhao Jiang Yi Ma Manzoor Ahmed Zenggang Xiong Yuanlin Lyu school of computer and Information Science Hubei Engineering UniversityXiaogan432000China school of computer Science and Information engineering Hubei UniversityWuhan430062China Artificial Intelligence Industrial Technology Research Institute Hubei Engineering UniversityXiaogan432000China

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

关键词： SIoT data forwarding social attributes social relations community

BSTFNet:An Encrypted Malicious Traffic Classification Method Integrating Global Semantic and Spatiotemporal Features

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computers, Materials & Continua 2024年第3期78卷 3929-3951页

作者： Hong Huang Xingxing Zhang Ye Lu Ze Li Shaohua Zhou school of computer Science and engineering Sichuan University of Science&EngineeringYibin644002China school of Mathematics and Statistics Sichuan University of Science&EngineeringYibin644002China

While encryption technology safeguards the security of network communications,malicious traffic also uses encryption protocols to obscure its malicious behavior.To address the issues of traditional machine learning methods relying on expert experience and the insufficient representation capabilities of existing deep learning methods for encrypted malicious traffic,we propose an encrypted malicious traffic classification method that integrates global semantic features with local spatiotemporal features,called BERT-based Spatio-Temporal Features Network(BSTFNet).At the packet-level granularity,the model captures the global semantic features of packets through the attention mechanism of the Bidirectional Encoder Representations from Transformers(BERT)model.At the byte-level granularity,we initially employ the Bidirectional Gated Recurrent Unit(BiGRU)model to extract temporal features from bytes,followed by the utilization of the Text Convolutional Neural Network(TextCNN)model with multi-sized convolution kernels to extract local multi-receptive field spatial features.The fusion of features from both granularities serves as the ultimate multidimensional representation of malicious traffic.Our approach achieves accuracy and F1-score of 99.39%and 99.40%,respectively,on the publicly available USTC-TFC2016 dataset,and effectively reduces sample confusion within the Neris and Virut categories.The experimental results demonstrate that our method has outstanding representation and classification capabilities for encrypted malicious traffic.

关键词： Encrypted malicious traffic classification bidirectional encoder representations from transformers text convolutional neural network bidirectional gated recurrent unit

Dynamical pattern recognition for univariate time series and its application to an axial compressor

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control Theory and Technology 2024年第1期22卷 39-55页

作者： Jingtao Hu Weiming Wu Zejian Zhu Cong Wang Center for Intelligent Medical engineering School of Control Science and TechnologyShandong UniversityJinan250061ShandongChina school of Automation Science and engineering South China University of TechnologyGuangzhou510641GuangdongChina

In this paper, a learning and recognition approach is proposed for univariate time series composed of output measurements of general nonlinear dynamical systems. Firstly, a class of dynamical systems in the canonical form is derived to describe the univariate time series by introducing coordinate transformation. An observer-based deterministic learning technique is then adopted to achieve dynamical modeling of the associated transformed systems of the training univariate time series, and the modeling results in the form of radial basis function network (RBFN) models are stored in a pattern library. Subsequently, multiple observer-based dynamical estimators containing the RBFN models in the pattern library are constructed for a test univariate time series, and a recognition decision scheme is proposed by the derived recognition indicator. On this basis, more concise recognition conditions are provided, which is beneficial for verifying the recognition results. Finally, simulation studies on the Rossler system and aero-engine stall warning verify the effectiveness of the proposed approach.

关键词： Dynamical pattern recognition Deterministic learning Stall warning Radial basis function network Sampled-data observer

High-rate metal-free MXene microsupercapacitors on paper substrates

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Carbon Energy 2024年第5期6卷 94-104页

作者： Han Xue Po‐Han Huang Lee‐Lun Lai Yingchun Su Axel Strömberg Gaolong Cao Yuzhu Fan Sergiy Khartsev Mats Göthelid Yan‐Ting Sun Jonas Weissenrieder Kristinn BGylfason Frank Niklaus Jiantong Li school of Electrical engineering and computer Science KTH Royal Institute of TechnologyStockholmSweden school of engineering Sciences KTH Royal Institute of TechnologyStockholmSweden

MXene is a promising energy storage material for miniaturized microbatteries and microsupercapacitors(MSCs).Despite its superior electrochemical performance,only a few studies have reported MXene-based ultrahigh-rate(>1000 mV s^(−1))on-paper MSCs,mainly due to the reduced electrical conductance of MXene films deposited on paper.Herein,ultrahigh-rate metal-free on-paper MSCs based on heterogeneous MXene/poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)(PEDOT:PSS)-stack electrodes are fabricated through the combination of direct ink writing and femtosecond laser scribing.With a footprint area of only 20 mm^(2),the on-paper MSCs exhibit excellent high-rate capacitive behavior with an areal capacitance of 5.7 mF cm^(−2)and long cycle life(>95%capacitance retention after 10,000 cycles)at a high scan rate of 1000 mV s^(−1),outperforming most of the present on-paper MSCs.Furthermore,the heterogeneous MXene/PEDOT:PSS electrodes can interconnect individual MSCs into metal-free on-paper MSC arrays,which can also be simultaneously charged/discharged at 1000 mV s^(−1),showing scalable capacitive performance.The heterogeneous MXene/PEDOT:PSS stacks are a promising electrode structure for on-paper MSCs to serve as ultrafast miniaturized energy storage components for emerging paper electronics.

关键词： direct ink writing femtosecond laser scribing MXene on-paper microsupercapacitors PEDOT:PSS ultrahigh rate capability

Double integral-enhanced Zeroing neural network with linear noise rejection for time-varying matrix inverse

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 197-210页

作者： Bolin Liao Luyang Han Xinwei Cao Shuai Li Jianfeng Li College of computer Science and engineering Jishou UniversityJishouChina school of Management Shanghai UniversityShanghaiChina school of engineering Swansea UniversitySwanseaUK

In engineering fields,time-varying matrix inversion(TVMI)issue is often encountered.Zeroing neural network(ZNN)has been extensively employed to resolve the TVMI problem.Nevertheless,the original ZNN(OZNN)and the integral-enhanced ZNN(IEZNN)usually fail to deal with the TVMI problem under unbounded noises,such as linear noises.Therefore,a neural network model that can handle the TVMI under linear noise interference is urgently needed.This paper develops a double integral-enhanced ZNN(DIEZNN)model based on a novel integral-type design formula with inherent linear-noise tolerance.Moreover,its convergence and robustness are verified by deriva-tion strictly.For comparison and verification,the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments.The experi-ments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises.In general,the DIEZNN model is an innovative work and is proposed for the first time.Satisfyingly,the errors of DIEZNN are always less than 1�10−3 under linear noises,whereas the error norms of OZNN and IEZNN models are not convergent to zero.In addition,these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.

关键词： neural network real-time systems

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 designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It 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 time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical 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

Effect of applied electric fields on supralinear dendritic integration of interneuron

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Chinese Physics B 2024年第2期33卷 84-95页

作者：樊亚琴魏熙乐卢梅丽伊国胜 Tianjin Key Laboratory of Process Measurement and control School of Electrical and Information EngineeringTianjin UniversityTianjin 300072China school of Information Technology engineering Tianjin University of Technology and EducationTianjin 300222China

Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs.Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic integration.At first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic output.By performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic integration.It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike.Also,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses.Furthermore,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.

关键词： GABAergic interneuron electrical field supralinear dendritic integration action potential generation