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Resilient sliding mode control for 2D CPSs under denial-of-service attacks

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science China(Information sciences) 2024年第6期67卷 262-278页

作者： Lingling LI Rongni YANG Zhiguang FENG Ligang WU College of Intelligent systems science and Engineering Harbin Engineering University school of Control science and Engineering Shandong University school of Astronautics Harbin Institute of Technology

This study addresses the resilient sliding mode control(SMC) problem for two-dimensional cyber-physical systems(2D CPSs) characterized by the Roesser model under denial-of-service attack(DoSA), which can interfere with signal transmission over the communication network. First, the DoS-A model is established by introducing constraints on the Do S frequency and duration. Then, based on active or silent attack situations, the considered system is described as a switched mode. Furthermore, together with Lyapunov theory, the average dwell time technique is employed to deduce sufficient criteria that assure the existence of the desired sliding mode controller. Finally, verification examples are provided to show the validity of the established SMC scheme.

关键词： two-dimensional systems cyber-physical systems denial-of-service attack resilient sliding mode control

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Threshold Selection and Resource Allocation for Quantized Identification

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Journal of systems science & Complexity 2024年第1期37卷 204-229页

作者： WANG Ying LI Xin ZHAO Yanlong ZHANG Ji-Feng Key Laboratory of systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China school of Mathematical sciences University of Chinese Academy of SciencesBeijing 100049China

This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first-order asymptotically optimal quantized identification theory is extended to the weak persistent excitation condition. Secondly, the characteristics of time and space complexities are established based on the Cramér-Rao lower bound of quantized systems. On these basis, the optimal selection methods of fixed thresholds and adaptive thresholds are established under aperiodic signals, which answer how to achieve the best efficiency of quantized identification under the same time and space complexity. In addition, based on the principle of maximizing the identification efficiency under a given resource, the optimal resource allocation methods of quantized identification are given for the cases of fixed thresholds and adaptive thresholds, respectively, which show how to balance time and space complexity to realize the best identification efficiency of quantized identification.

关键词： Quantized output resource allocation system identification threshold selection.

systems science in the new era: intelligent systems and big data

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science China(Information sciences) 2024年第3期67卷 308-310页

作者： Wenwu YU Duxin CHEN Hongzhe LIU He WANG Jinde CAO Zengru DI Xiaojun DUAN Bin JIA Xiaodong DING Yiguang HONG school of Mathematics Southeast University Purple Mountain Laboratories International Academic Center of Complex systems Beijing Normal University College of science National University of Defense Technology school of systems science Beijing Jiaotong University Business school University of Shanghai for Science and Technology Department of Control science and Engineering Tongji University

This study introduces the emergence, research challenges,and future development of intelligent systems and big data(ISBD) and discusses the significance of ISBD to systems science. To this end, an overview of systems science is first presented, followed by the conclusion that the development of artificial intelligence(AI) has promoted the derivation and development of intelligent systems(ISs).

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Compensated acceleration feedback based active disturbance rejection control for launch vehicles

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Chinese Journal of Aeronautics 2024年第4期37卷 464-478页

作者： Xiaoyan ZHANG Wenchao XUE Zibo LIU Ran ZHANG Huifeng LI Key Laboratory of systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China school of Mathematical sciences University of Chinese Academy of SciencesBeijing 100049China school of Astronautics Beihang UniversityBeijing 100191China

In this paper, the attitude tracking and load relief control problems against wind disturbances and uncertain aerodynamics as well as the engine thrust of launch vehicles are ***, a framework of Compensated Acceleration Feedback based Active Disturbance Rejection Control(CAF-ADRC) is established to achieve both desired attitude tracking and load relief performances. In particular, the total disturbance that includes the effects caused by both aerocoefficient perturbations and disturbances is estimated by constructing an Extended State Observer(ESO) to achieve attitude tracking. Furthermore, combined with the normal acceleration due to the engine thrust, the accelerometer measurement is also compensated to enhance the load relief ***, the quantitative analysis of ESO and the entire closed-loop system are studied. It can be concluded that the desired attitude tracking and load relief performances can be achieved simultaneously under the proposed approach. Besides, tuning laws of the proposed approach are systematically given, which are divided into ESO, Proportional Derivative(PD) and Compensated Acceleration Feedback(CAF) modules. Moreover, the performances under CAF-ADRC approach can be better than those under CAF based PD(CAF-PD) approach by tuning load relief ***, the approach presented is applied to a typical control problem of launch vehicles with wind disturbances and parameter uncertainties.

关键词： Launch vehicles Uncertainty analysis Active disturbance rejection control(ADRC) Load relief control Extended state observer(ESO)

On the convergence of tracking differentiator with multiple stochastic disturbances

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science China(Information sciences) 2024年第2期67卷 157-169页

作者： Zehao WU Huacheng ZHOU Baozhu GUO Feiqi DENG school of Mathematics and Big Data Foshan University school of Mathematics and Statistics Central South University Academy of Mathematics and systems science Chinese Academy of Sciences systems Engineering Institute South China University of Technology

This paper investigates the convergence, noise-tolerance, and filtering performance of a tracking differentiator in the presence of multiple stochastic disturbances for the first time. We consider a general case wherein the input signal is corrupted by additive colored noise, and the tracking differentiator is disturbed by additive colored noise and white noise. The tracking differentiator is shown to track the input signal and its generalized derivatives in the mean square sense. Further, the almost sure convergence can be achieved when the stochastic noise affecting the input signal is vanishing. Herein, numerical simulations are performed to validate the theoretical results.

关键词： tracking differentiator convergence noise-tolerance filtering performance multiple stochastic disturbances

Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

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Computers, Materials & Continua 2024年第3期78卷 3469-3487页

作者： Sureka Sivavelu Venkatesh Palanisamy school of Computer science Engineering and Information systems Vellore Institute of TechnologyVellore632014India

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two sta

关键词： Software defect prediction feature selection nonparametric statistical Torgerson-Gower scaling technique quadratic censored regressive convolution deep neural network softstep activation function nelder-mead method

2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

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Computer Modeling in Engineering & sciences 2024年第8期140卷 2035-2051页

作者： Sandeep Dasari Rajesh Kaluri school of Computer science Engineering and Information systems Vellore Institute of TechnologyVellore632014India

The increasing data pool in finance sectors forces machine learning(ML)to step into new *** data has significant financial implications and is *** users data from several organizations for various banking services may result in various intrusions and privacy *** a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global ***,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of *** address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global *** improves the privacy of the local *** analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)***,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and *** experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

关键词： Federated learning FedAvg FedProx flower framework privacy preservation financial sectors

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

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Chimera states of phase oscillator populations with nonlocal higher-order couplings

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Chinese Physics B 2024年第4期33卷 402-407页

作者：伍勇刚余华健郑志刚徐灿 school of Mathematical sciences Huaqiao UniversityQuanzhou 362021China Institute of systems science and College of Information science and Engineering Huaqiao UniversityXiamen 361021China

The chimera states underlying many realistic dynamical processes have attracted ample attention in the area of dynamical ***, we generalize the Kuramoto model with nonlocal coupling incorporating higher-order interactions encoded with simplicial *** works have shown that higher-order interactions promote coherent ***, we uncover the fact that the introduced higher-order couplings can significantly enhance the emergence of the incoherent ***, we identify that the chimera states arise as a result of multi-attractors in dynamic ***, we review that the increasing higher-order interactions can significantly shape the emergent probability of chimera *** the observed results can be well described in terms of the dimension reduction *** study is a step forward in highlighting the importance of nonlocal higher-order couplings, which might provide control strategies for the occurrence of spatial-temporal patterns in networked systems.

关键词： synchronization complex system coupled oscillators phase transition