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2020 2nd International Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2020

作者： Mo, Dai Li Yu, Zhi Hua Cai, Yun Fei Liu, Rui School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

This paper presents a novel method of distinguishing signal, the way expected to reduce the nuisance alarm rate since the high nuisance alarm rate will restrict the capability of phase-sensitive optical time-domain reflection technology. The proposed method includes two parts: wavelet positioning mutation to obtain the perturbation area and Pearson correlation algorithm to directly convert the intensity of the perturbation into a useful amplitude. This technique avoids the use of irrelevant data in these differential signals and provides a simple and feasible new approach for distinguishing signal and optimizing the positioning speed of f-OTDR systems. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Time domain analysis

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Stabilization of discrete time stochastic linear systems with time delay via event-triggered control

Stabilization of discrete time stochastic linear systems wit...

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2021 China automation Congress, CAC 2021

作者： Dong, Jian Zong, Xiaofeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

This paper presents the stabilization problem of a class of discrete-time stochastic linear systems with time delay using an event-triggered control(ETC) strategy. For the general linear systems, we propose a new event triggering mechanism and deduce sufficient conditions for mean square exponentially stabilizability(MSES) and almost sure exponentially stabilizability(ASES) via ETC. The results show that the stability of the system depends on the system parameters (time delay, noise, event trigger threshold parameter, and unstable characteristic value of the original system). When the feedback control is disturbed by low-intensity noise, the unstable system can be stable in the mean square. Finally, the validity of the theoretical results is illustrated through a simulation example. © 2021 IEEE

关键词： Linear systems

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Dynamic analysis and control of fractional order memristor Hopfield neural network

Dynamic analysis and control of fractional order memristor H...

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第42届中国控制会议

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network(fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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Coverage control of Unmanned Aerial Vehicles for Periodical Monitoring of Geohazards

Coverage Control of Unmanned Aerial Vehicles for Periodical ...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Zhang, Wei Zhai, Chao School of Automation China University of Geosciences Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Ministry of Education Wuhan430074 China

ISBN: (纸本)9780738146577

Landslides have become one of the major hazards endangering the lives and property of people all over the world. In order to improve the early warning of geohazards, a cooperative coverage control algorithm of unmanned aerial vehicles (UAV) is developed in this paper. The proposed control algorithm is integrated with the airborne radar to periodically monitor the surface deformation, which is closely related to the emergence of geohazards. A Lyapunov function is constructed to ensure the stability of UAVs driven by the proposed control algorithm. Numerical simulations are conducted to substantiate the coverage control approach for UAVs in the uncertain environment. This work provides new insight into the effective monitoring and early warning of geohazards with the assistance of UAVs. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Automatic Target Recognition in GPR Images Based on Time-Frequency Texture Features and Support Vector Machine

Automatic Target Recognition in GPR Images Based on Time-Fre...

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2021 China automation Congress, CAC 2021

作者： Chen, Kehui Xue, Wei Wang, Zexi Ma, Shaopeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

Ground penetrating radar (GPR) images are easily disturbed by noise, which causes a lot of difficulties for target recognition. To improve the target recognition performance in GPR images, a novel recognition method based on time-frequency texture features and support vector machine (SVM) is proposed. The proposed method first extracts texture features from the gray co-occurrence matrix of S transform time-frequency images for the A-scan data, then establishes the SVM model and realizes the target recognition. The proposed method is assessed using synthetic GPR images and compared with other two time-frequency analysis methods, combined with SVM. The expermental results show that the proposed method can achieve higher recognition accuracies than the other two methods in heavily noisy environment. © 2021 IEEE

关键词： Support vector machines

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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第42届中国控制会议

作者： Malak Abid Ali Khan Hongbin Ma Ying Jin Jingxiang Ma Zia Ur Rehman Mizanur Rahman School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

Deforestation is the primary source of global warming;traditional shelf labels use paper to display the price of the products,and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its *** technologies provide connectivity and a fast-updating system to eliminate the paper-based *** is one of the contenders to design the system for electronic shelf labels(ESLs).In this paper,LoRa has been used to minify data losses and guarantee the successful decoding of the carrier *** data parallelism at the network server(NS) is used to distribute the data packets among the gateways(GWs) for concurrent transmissions to the end devices(EDs).The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and *** data rate(DR) and spreading factors(SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated *** orthogonality principles follow industrial,scientific,and medical regulations(ISM) to avoid data traffic *** under different duty cycles(DC) and bandwidth(BW) are examined to minify the network saturation and reduce the energy harvesting of the tags.

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

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第42届中国控制会议

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

Based on fractional calculus theory and reaction-diffusion equation theory,a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is *** constructing the phase space basis based on the Laplace operator eigenvector,the system equation is linearized to obtain the characteristic ***,the characteristic equation is analyzed,and the local stability of the system at the equilibrium point is *** taking the time delay as the bifurcation parameter,the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay ***,a state feedback controller is designed to control the bifurcation of the ***,the theoretical derivation is verified by numerical simulation.

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Tan, Qingshan Li, Changhe Zeng, Sanyou Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9798350314588

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front. © 2023 IEEE.

关键词： Multiobjective optimization

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Dynamic State Estimation for Power System with Communication Constraint Using Event-Triggered Cubature Kalman Filter

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Journal of Beijing Institute of Technology (English Edition) 2021年第zk期30卷 129-140页

作者： Wei, Minfeng Xu, Min Zhang, Fengdi School of Automation and Key Laboratory for Intelligent Control and Decision on Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

Accurate dynamic state estimation plays an important role in power systems. Although various filtering algorithms, such as unscented Kalman filter (UKF) and particle filter (PF), have been proposed based on phasor measurement units (PMUs), they occupy a huge communication bandwidth without specific concern, which puts heavy burden on the communication network especially when wireless communications are widely applied in smart grids. In order to relieve this communication burden, the event-triggered cubature Kalman filter (ETCKF) is proposed based on the stochastic event-triggered schedule in this paper, which guarantees that only the measurements containing innovational information are transmitted and has advantages over other event-triggered schedules, such as the deterministic event-triggered schedule, since it can maintain the Gaussian property of the conditional distribution of the system state. Based on the developed nonlinear event-triggered schedule, the cubature Kalman filter (CKF), using the third-degree spherical-radial cubature rule, further provides more accurate estimation than UKF and has lower computational complexity than PF. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 39-bus system is utilized to verify the feasibility and performance of the proposed method. © 2020 Journal of Beijing Institute of Technology

关键词： Phasor measurement units

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Multiple–Model UKF/CKF State Estimation for Nonlinear systems

Multiple–Model UKF/CKF State Estimation for Nonlinear Syste...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Shi, Xiaodi Yan, Liping Xia, Yuanqing Xiao, Bo Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811581540

In most control systems, modeling error and noise interference will always lead to the performance degradation and divergence of the UKF or the CKF. To settle a matter caused by model uncertainties, a new UKF/CKF frame combined with multiple model method is presented in this paper. Through probabilistic multiple model design method, this paper approximates the posterior densities by a finite number of probabilistically weighted points and uses these points to display the entire state space. Simulation results and comparison analysis demonstrate that the multiple-model UKF(MMUKF) and the multiple-model CKF(MMCKF) have higher precision and stronger robustness than the traditional UKF and CKF in case of model uncertainties. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Uncertainty analysis

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