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SSRN 2024年

作者： Lv, Weilin Nie, Wansui Wei, Jun Zhang, Jianjun Meng, Chuizhou Liu, Teng Sui, Jin Guo, Shijie Engineering Research Center The Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies Hebei University of Technology Tianjin300401 China Hebei Provincial Key Laboratory of Robot Perception and Human-Machine Fusion Hebei University of Technology Tianjin300401 China School of Mechanical Engineering Hebei University of Technology Tianjin300401 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

Kirigami has been utilized in designing deployable mechanisms for various engineering applications. This paper presents a novel construction method for one-degree-of-freedom (1-DOF) multi-loop kirigami mechanisms whose folding motions are kinematically equivalent to their original degree-4 rigid origami. Firstly, we introduce a family of single-loop kirigami (SLK) as the main loop of 1-DOF multi-loop kirigami. Secondly, the coupling-constraint properties of multi-DOF SLKs are clarified, and the structural characteristics of the 1-DOF multi-loop kirigami are defined, based on which, the construction method for the 1-DOF multi-loop kirigami is proposed. Thirdly, the representative models are selected and their kinematics are presented to demonstrate their capability to achieve folding motion equivalent to their origami prototypes, thus verifying the validity of our proposed methodology. Fourthly, the non-constraint condition of the 1-DOF multi-loop kirigami is presented. Finally, we propose extended configurations of 1-DOF multi-loop kirigami and provide the forward and inverse design methods for constructing kirigami meshes. The proposed methodology facilitates the design of large-scale deployable structures. © 2024, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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Morphological component analysis based on mixed dictionary for signal denoising of ground penetrating radar

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International Journal of Simulation and process Modelling 2019年第5期14卷 431-441页

作者： Zhang, Jianhua Zhang, Haohao Li, Yang Wu, Xueli Hebei Provincial Research Center for Technologies in Process Engineering Automation Shijiazhuang Hebei University of Science and Technology Hebei050018 China Hebei University of Science and Technology Hebei Shijiazhuang050018 China

Forward modelling is applied to simulate the ground penetrating radar (GPR) detection environment, and a modified morphological component analysis (MCA) algorithm is applied to GPR signal denoising. Finite-difference time-domain (FDTD) method is used to perform finite difference approximation to the space and time derivatives of Maxwell's equations. Under the forward simulation framework, the MCA algorithm applies a sparse dictionary to decompose the GPR signal. However, clutter is not represented as there is no corresponding sparse dictionary, the clutter is removed when the signal is reconstructed. The core of the MCA is to select a suitable dictionary. The combination of undecimated discrete wavelet transform (UDWT) dictionary and curvelet transform dictionary (CURVELET) is selected. The improved MCA algorithm is compared with singular value decomposition (SVD) and principal component analysis (PCA), to confirm the high performance of the proposed algorithm. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Maxwell equations

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Simulation of multilateration system based on Chan algorithm and conjugate gradient optimisation algorithm

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International Journal of Simulation and process Modelling 2019年第5期14卷 464-473页

作者： Zhang, Jianhua Gao, Feng Li, Yang Wu, Xueli Hebei Provincial Research Center for Technologies in Process Engineering Automation Hebei University of Science and Technology Shijiazhuang Hebei050018 China Hebei University of Science and Technology Shijiazhuang Hebei050018 China

In multilateration (MLAT) systems, the traditional Chan algorithm applies the theory of time-difference-of-arrival (TDOA) to solve the target position of the mathematical model. By introducing intermediate variables, the algorithm adopts a two-step weighted least-squares solution. The introduction of intermediate variables results in the target position equation producing a fuzzy solution, this reduces positioning accuracy. The conjugate gradient algorithm (CGA) is one of the most useful methods for solving large linear equations, it avoids solving the inverse of the matrix, whilst it 'speeds up' the solution of the target position. A four stations multi-point-positioning system mathematical model is established, and a new fusion algorithm Chan-CGA is applied to the MLAT system. Finally, the fusion algorithm is evaluated by simulation and compared with the Chan-Taylor algorithm. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Time difference of arrival

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Ground Penetrating Radar Signal processing Based on Morphological Component Analysis

Ground Penetrating Radar Signal Processing Based on Morpholo...

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10th International Conference on Modelling, Identification and Control, ICMIC 2018

作者： Zhang, Jianhua Zhang, Haohao Li, Yang Gao, Feng Wu, Xueli Zhu, Feng Hebei University of Science and Technology Shijiazhuang Hebei 050018 China Hebei Provincial Research Center for Technologies in Process Engineering Automation Shijiazhuang Hebei 050018 China CCCC-FHDI ENGINEERING CO.LTD China

ISBN: (纸本)9781538654163

Ground-penetrating radar (GPR) is one of the most popular underground detection devices and has a wide range of applications. However, when using GPR to detect targets, since targets are located near the surface, the influence of clutter on target detection is very serious. Especially in some complex environments, targets may be completely covered by clutter. Thus, clutter reduction is the primary task. Singular value decomposition (SVD), principal component analysis (PCA) and independent component analysis (ICA) are commonly used for target detection. In this paper, a method based on morphological component analysis (MCA) is adopted, and a decomposition model is proposed to distinguish between target and clutter. Finally, it is proved by visual simulation that this method is superior to other methods in removing clutter. © 2018 IEEE.

关键词： Geophysical prospecting

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research on UAV Conflict Resolution Algorithm Based on Improved Particle Swam Algorithm

Research on UAV Conflict Resolution Algorithm Based on Impro...

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Jianhua Zhang Shuangcheng Dou Yang Li Xueli Wu Ran Zhen Kai Gao Dongwen Zhang Hebei University of Science and Technology Hebei Provincial Research Center for Technologies in Process Engineering Automation Shijiazhuang Hebei China

This paper is based on the safety method of particle swarm, and integrates the classical particle swarm algorithm and simulated annealing particle swarm algorithm. This article combines the classic particle swarm algorithm and simulated annealing particle swarm optimization algorithm, the advantages of can improve the UAV mission in a complex spatial environment safety, reduce the unmanned aerial vehicle unable to effectively avoid the ground fixed obstacles in the process of flying and air other aircraft due to the risk of collision, made it possible to unmanned aerial vehicles and man-machine Shared airspace, able to perform various tasks for unmanned aerial vehicle safely and successfully provide effective protection.

关键词： Unmanned aerial vehicles Particle swarm optimization Simulated annealing Convergence Heuristic algorithms automation

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A General U-Model Based Adaptive Control Design Procedure for Nonlinear Non-affine Systems

A General U-Model Based Adaptive Control Design Procedure fo...

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第37届中国控制会议

作者： Jianhua Zhang Quanmin Zhu Yang Li Xueli Wu Feng Gao Hebei University of Science and Technology Hebei Provincial Research Center for Technologies in Process Engineering Automation Department of Engineering Design and Mathematics University of the West of England

In this study, a general U-model based design procedure is expanded to adaptive super twisting control of nonlinear polynomial systems, which is named as U-super adaptive twisting control in short. By using the estimator, an adaptive regulator for a class of simple discrete time systems with bounded disturbance is presented, discrete time super twisting reference model is proposed with proper convergence precision and convergence time for nonlinear dynamic plants including non-affine systems. Two bench test examples(non-affine plants which could be very challenging to design such control systems using the other approaches) are selected to demonstrate the feasibility and effectiveness with computational experiments, which the case studies could be guidance for readers/users with their ad hoc applications.

关键词： U-model U-model enhanced control super twisting control U-robust adaptive control non-affine systems

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Notice of Violation of IEEE Publication Principles: Ground Penetrating Radar Signal processing Based on Morphological Component Analysis

Notice of Violation of IEEE Publication Principles: Ground P...

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Jianhua Zhang Haohao Zhang Yang Li Feng Gao Xueli Wu Feng Zhu Hebei University of Science and Technology Shijiazhuang Hebei 050018China Hebei Provincial Research Center for Technologies in Process Engineering Automation Shijiazhuang Hebei China CCCC-FHDI ENGINEERING CO.LTD

Notice of Violation of IEEE Publication Principles "Ground Penetrating Radar Signal processing Based on Morphological Component Analysis" by J. Zhang, H. Zhang, Y. Li, F. Gao, X. Wu, and F. Zhu in the Proceedings of the 10th International Conference on Modelling, Identification and Control (ICMIC), July 2018, pp.1-6 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper copied portions of text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. "Clutter Removal in Ground-Penetrating Radar Images Using Morphological Component Analysis" by Eyyup Temlioglu and Isin Erer in IEEE Geoscience and Remote Sensing Letters, December 2016, pp.1802-1806 Ground-penetrating radar (GPR) is one of the most popular underground detection devices and has a wide range of applications. However, when using GPR to detect targets, since targets are located near the surface, the influence of clutter on target detection is very serious. Especially in some complex environments, targets may be completely covered by clutter. Thus, clutter reduction is the primary task. Singular value decomposition (SVD), principal component analysis (PCA) and independent component analysis (ICA) are commonly used for target detection. In this paper, a method based on morphological component analysis (MCA) is adopted, and a decomposition model is proposed to distinguish between target and clutter. Finally, it is proved by visual simulation that this method is superior to other methods in removing clutter.

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A General U-Model Based Super Twisting Design Procedure for Nonlinear Polynomial Systems 36

A General U-Model Based Super Twisting Design Procedure for ...

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第36届中国控制会议

作者： Jianhua Zhang Quanmin Zhu Yang Li Xueli Wu Ran Zhen Hebei University of Science and Technology Hebei Provincial Research Center for Technologies in Process Engineering Automation Department of Engineering Design and Mathematics University of the West of England

ISBN: (纸本)9781538629185

In this study,a general U-model based design procedure is expanded to super twisting control of nonlinear polynomial systems,which is named as U-super twisting control in short.A discrete time super twisting reference model is proposed with proper convergence precision and convergence time for nonlinear dynamic plants including non-affine *** bench test examples（non-affine plants which could be very challenging to design such control systems using the other approaches） are selected to demonstrate the feasibility and effectiveness with computational experiments,which the case studies could be guidance for readers/users with their ad hoc applications.

关键词： U-model U-model enhanced control super twisting control U-super twisting control nonlinear systems non-affine systems

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Real-time multimodal transport path planning based on a pulse neural network model

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International Journal of Simulation and process Modelling 2017年第3-4期12卷 356-361页

作者： Zhao, Tongjuan Wang, Jiuhe Zhang, Jianhua Yanshan University Qinhuangdao Hebei066004 China Qinhuangdao Vocational and Technical College Qinhuangdao Hebei066100 China Hebei University of Science and Technology Shijiazhuang Hebei050018 China Hebei Provincial Research Center for Technologies in Process Engineering Automation Shijiazhuang Hebei050018 China

A modified pulse-coupled neural network (MPCNN) model is designed for real-time collision-free path planning of multimodal transport choice in stationary or non-stationary environments. The proposed neural network is topologically organised with only local lateral connections among neurons. The optimisation networks model consists of transport distance, transport time, transit costs and transit time and other factors, and then all factors compose to weight of the networks to realise the transformation to solve the shortest path problem. The effectiveness and efficiency of the proposed approach is demonstrated through simulation and comparison studies. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Wave propagation

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Super Twisting sliding mode control of nonlinear system based on U model control 35

Super Twisting sliding mode control of nonlinear system base...

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第35届中国控制会议

作者： ZHANG Jianhua WU Xueli LI Yang HUO Jianan Hebei University of Science and Technology Hebei Provincial Research Center for Technologies in Process Engineering Automation Yanshan University

ISBN: (纸本)9781509009107

In this thesis,the Super-Twisting control algorithm is used to analyze the nonlinear control system based on U *** non-affine nonlinear systems are described,and the 1-order and n-order nonlinear system is *** neural network approximation of the nonlinear function is performed by Super-Twisting control *** convergence of Super-Twisting algorithm is proved by the appropriate Lyapunov *** order to verify the feasibility and effectiveness of the proposed method,the results show that the output of the controlled system can be tracked in a very short time by using the Super-Twisting controller,and the output of the controlled system can improve the robustness of the system.

关键词： Nonlinear system neural network U model Super-Twisting algorithm

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