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Two simple memristive maps with adaptive energy regulation ano digital signal process verification

Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第5期25卷 382-394页

作者： Feifei YANG Lujie REN Jun MA Zhigang ZHU college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050China Department of Physics Lanzhou University of TechnologyLanzhou 730050China School of information Science and engineering Dalian Polytechnic UniversityDalian 116034China

Mathematical models can produce desired dynamics and statistical properties with the insertion of suitable nonlinear terms,while energy characteristics are crucial for practical application because any hardware realizations of nonlinear systems are relative to energy flow.The involvement of memristive terms relative to memristors enables multistability and initial-dependent property in memristive systems.In this study,two kinds of memristors are used to couple a capacitor or an inductor,along with a nonlinear resistor,to build different neural circuits.The corresponding circuit equations are derived to develop two different types of memristive oscillators,which are further converted into two kinds of memristive maps after linear transformation.The Hamilton energy function for memristive oscillators is obtained by applying the Helmholz theorem or by mapping from the field energy of the memristive circuits.The Hamilton energy functions for both memristive maps are obtained by replacing the gains and discrete variables for the memristive oscillator with the corresponding parameters and variables.The two memristive maps have rich dynamic behaviors including coherence resonance under noisy excitation,and an adaptive growth law for parameters is presented to express the self-adaptive property of the memristive maps.A digital signal process(DSP)platform is used to verify these results.Our scheme will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map-energy calculation.

关键词： Hamilton energy Discrete memristor Self-adaptive regulation Digital signal process(DSP)implementation

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A method for cleaning wind power anomaly data by combining image processing with community detection algorithms

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Global Energy Interconnection 2024年第3期7卷 293-312页

作者： Qiaoling Yang Kai Chen Jianzhang Man Jiaheng Duan Zuoqi Jin college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050P.R.China

Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data.Consequently,a method for cleaning wind power anomaly data by combining image processing with community detection algorithms(CWPAD-IPCDA)is proposed.To precisely identify and initially clean anomalous data,wind power curve(WPC)images are converted into graph structures,which employ the Louvain community recognition algorithm and graph-theoretic methods for community detection and segmentation.Furthermore,the mathematical morphology operation(MMO)determines the main part of the initially cleaned wind power curve images and maps them back to the normal wind power points to complete the final cleaning.The CWPAD-IPCDA method was applied to clean datasets from 25 wind turbines(WTs)in two wind farms in northwest China to validate its feasibility.A comparison was conducted using density-based spatial clustering of applications with noise(DBSCAN)algorithm,an improved isolation forest algorithm,and an image-based(IB)algorithm.The experimental results demonstrate that the CWPAD-IPCDA method surpasses the other three algorithms,achieving an approximately 7.23%higher average data cleaning rate.The mean value of the sum of the squared errors(SSE)of the dataset after cleaning is approximately 6.887 lower than that of the other algorithms.Moreover,the mean of overall accuracy,as measured by the F1-score,exceeds that of the other methods by approximately 10.49%;this indicates that the CWPAD-IPCDA method is more conducive to improving the accuracy and reliability of wind power curve modeling and wind farm power forecasting.

关键词： Wind turbine power curve Abnormal data cleaning Community detection Louvain algorithm Mathematical morphology operation

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Memristive oscillator to memristive map,energy characteristic

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Science China(Technological Sciences) 2024年第5期67卷 1567-1578页

作者： GUO YiTong MA Jun ZHANG XiaoFeng HU XiKui college of Electrical and information engineering Lanzhou University of TechnologyLanzhou730050China Department of Physics Lanzhou University of TechnologyLanzhou730050China School of Science Chongqing University of Posts and TelecommunicationsChongqing400065China

Most of nonlinear oscillators composed of capacitive and inductive variables can obtain the Hamilton energy by using the Helmholtz theorem when the models are rewritten in equivalent vector forms.The energy functions for biophysical neurons can be obtained by applying scale transformation on the physical field energy in their equivalent neural circuits.Realistic dynamical systems often have exact energy functions,while some mathematical models just suggest generic Lyapunov functions,and the energy function is effective to predict mode transition.In this paper,a memristive oscillator is approached by two kinds of memristor-based nonlinear circuits,and the energy functions are defined to predict the dependence of oscillatory modes on energy level.In absence of capacitive variable for capacitor,the physical time t and charge q are converted into dimensionless variables by using combination of resistance and inductance(L,R),e.g.,τ=t×R/L.Discrete energy function for each memristive map is proposed by applying the similar weights as energy function for the memristive oscillator.For example,energy function for the map is obtained by replacing the variables and parameters of the memristive oscillator with corresponding variables and parameters for the memristive map.The memristive map prefers to keep lower average energy than the memristive oscillator,and chaos is generated in a discrete system with two variables.The scheme is helpful for energy definition in maps,and it provides possible guidance for verifying the reliability of maps by considering the energy characteristic.

关键词： Hamilton energy memristor Helmholtz theorem scale transformation memristive circuit

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Generalized load graphical forecasting method based on modal decomposition

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Global Energy Interconnection 2024年第2期7卷 166-178页

作者： Lizhen Wu Peixin Chang Wei Chen Tingting Pei college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050P.R.China School of Electrical Data engineering University of Technology SydneyNSW2007Australia

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.

关键词： Load forecasting Generalized load Image processing DenseNet Modal decomposition

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An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

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Communications in Theoretical Physics 2024年第3期76卷 42-50页

作者： Feifei Yang Ping Zhou Jun Ma School of Science Chongqing University of Posts and TelecommunicationsChongqing 430065China college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050China Department of Physics Lanzhou University of TechnologyLanzhou 730050China

Nonlinear circuits can show multistability when a magnetic flux-dependent memristor(MFDM) or a charge-sensitive memristor(CSM) is incorporated into a one branch circuit,which helps estimate magnetic or electric field effects.In this paper,two different kinds of memristors are incorporated into two branch circuits composed of a capacitor and a nonlinear resistor,thus a memristive circuit with double memristive channels is designed.The circuit equations are presented,and the dynamics in this oscillator with two memristive terms are discussed.Then,the memristive oscillator is converted into a memristive map by applying linear transformation on the sampled time series for the memristive oscillator.The Hamilton energy function for the memristive oscillator is obtained by using the Helmholtz theorem,and it can be mapped from the field energy of the memristive circuit.An energy function for the dual memristive map is suggested by imposing suitable weights on the discrete energy function.The dynamical behaviors of the new memristive map are investigated,and an adaptive law is proposed to regulate the firing mode in the memristive map.This work will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map energy calculation.

关键词： Hamilton energy dual memristive map adaptive energy regulation

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Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1605-1620页

作者： Yufeng Lian Xingtian Xiao Jiliang Zhang Long Jin Junzhi Yu Zhongbo Sun the Department of Control engineering Changchun University of TechnologyChangchun 130012China IEEE the college of information Science and engineering Northeastern UniversityShenyang 110819 the National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China the School of information Science and engineering Lanzhou UniversityLanzhou 730000China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

关键词： Cooperative motion control noise-tolerant zeroing neural network(NTZNN) omnidirectional mobile manipulator(OMM) repetitive motion planning

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Multi-Agent Deep Deterministic Policy Gradien-Based Task Offloading Resource Allocation Joint Offloading

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Journal of Computer and Communications 2024年第6期12卷 152-168页

作者： Xuan Zhang Xiaohui Hu college of Electronics and information engineering Lanzhou Jiaotong University Lanzhou China

With the advancement of technology and the continuous innovation of applications, low-latency applications such as drones, online games and virtual reality are gradually becoming popular demands in modern society. However, these applications pose a great challenge to the traditional centralized mobile cloud computing paradigm, and it is obvious that the traditional cloud computing model is already struggling to meet such demands. To address the shortcomings of cloud computing, mobile edge computing has emerged. Mobile edge computing provides users with computing and storage resources by offloading computing tasks to servers at the edge of the network. However, most existing work only considers single-objective performance optimization in terms of latency or energy consumption, but not balanced optimization in terms of latency and energy consumption. To reduce task latency and device energy consumption, the problem of joint optimization of computation offloading and resource allocation in multi-cell, multi-user, multi-server MEC environments is investigated. In this paper, a dynamic computation offloading algorithm based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is proposed to obtain the optimal policy. The experimental results show that the algorithm proposed in this paper reduces the delay by 5 ms compared to PPO, 1.5 ms compared to DDPG and 10.7 ms compared to DQN, and reduces the energy consumption by 300 compared to PPO, 760 compared to DDPG and 380 compared to DQN. This fully proves that the algorithm proposed in this paper has excellent performance.

关键词： Edge Computing Task Offloading Deep Reinforcement Learning Resource Allocation MADDPG

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Integrated multi-scale approach combining global homogenization and local refinement for multi-field analysis of high-temperature superconducting composite magnets

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 747-762页

作者： Hanxiao GUO Peifeng GAO Xingzhe WANG Key Laboratory of Mechanics on Western Disaster and Environment of Ministry of Education Key Laboratory of Special Function Materials and Structure Design of Ministry of EducationCollege of Civil Engineering and MechanicsLanzhou UniversityLanzhou 730000China

Second-generation high-temperature superconducting(HTS)conductors,specifically rare earth-barium-copper-oxide(REBCO)coated conductor(CC)tapes,are promising candidates for high-energy and high-field superconducting applications.With respect to epoxy-impregnated REBCO composite magnets that comprise multilayer components,the thermomechanical characteristics of each component differ considerably under extremely low temperatures and strong electromagnetic fields.Traditional numerical models include homogenized orthotropic models,which simplify overall field calculation but miss detailed multi-physics aspects,and full refinement(FR)ones that are thorough but computationally demanding.Herein,we propose an extended multi-scale approach for analyzing the multi-field characteristics of an epoxy-impregnated composite magnet assembled by HTS pancake coils.This approach combines a global homogenization(GH)scheme based on the homogenized electromagnetic T-A model,a method for solving Maxwell's equations for superconducting materials based on the current vector potential T and the magnetic field vector potential A,and a homogenized orthotropic thermoelastic model to assess the electromagnetic and thermoelastic properties at the macroscopic scale.We then identify“dangerous regions”at the macroscopic scale and obtain finer details using a local refinement(LR)scheme to capture the responses of each component material in the HTS composite tapes at the mesoscopic scale.The results of the present GH-LR multi-scale approach agree well with those of the FR scheme and the experimental data in the literature,indicating that the present approach is accurate and efficient.The proposed GH-LR multi-scale approach can serve as a valuable tool for evaluating the risk of failure in large-scale HTS composite magnets.

关键词： epoxy-impregnated high-temperature superconducting(HTS)magnet multi-scale method global homogenization(GH) local refinement(LR) multi-field analysis

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A simplified dispersion-compensation microstructure fiber with seven cores

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Optoelectronics Letters 2024年第4期20卷 216-221页

作者： LI Wenchao WANG Chao YANG Hongda HANG Ying WANG Wei Intelligence and information engineering college Tangshan UniversityTangshan 063000China School of information Science and engineering Yanshan UniversityQinhuangdao 066004China

In order to compensate the dispersion accumulated in a single mode fiber(SMF)for higher communication capacity,a simplified dispersion-compensation microstructure fiber(DC-MSF)with seven cores is proposed in this paper.The fiber’s cladding is made of pure silica without air holes,and its outer cores are composed of six germanium up-doped cylinders,which has the advantage of simple structure.The finite element method(FEM)and beam propagation method(BPM)are used to study the properties of the fiber,and the relationship between the structural parameters of the fiber and the dispersion,as well as the phase matching wavelength,is obtained.By optimizing the structural parameters of the fiber,the dispersion of the fiber can reach-5291.47 ps·nm^(-1)·km^(-1) at 1550 nm,and the coupling loss to the conventional single-mode fiber is only 0.137 d B.Compared with the conventional dispersion-compensation fiber,the fiber has lots of advantages,such as single mode transmission,easy to fabricate and low coupling loss with traditional SMF,etc.

关键词： fiber dispersion simplified

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Plasma nitrogen fixation system with dual-loop enhancement for improved energy efficiency and its efficacy for lettuce cultivation

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Plasma Science and Technology 2024年第1期26卷 82-92页

作者：韩泽阳张梦雪张頔何欣井天军葛知轩李玉鸽朱童任云鸿仲崇山季方 college of information and Electrical engineering China Agricultural UniversityBeijing 100083People’s Republic of China college of Water Resources and Civil engineering China Agricultural UniversityBeijing 100083People’s Republic of China Electric Power Research Institute State Grid Gansu Electric Power Company GansuLanzhou 730030People’s Republic of China

Plasma nitrogen fixation(PNF)has been emerging as a promising technology for greenhouse gasfree and renewable energy-based agriculture.Yet,most PNF studies seldom address practical application-specific issues.In this work,we present the development of a compact and automatic PNF system for on-site agricultural applications.The system utilized a gliding-arc discharge as the plasma source and employed a dual-loop design to generate NO_(x)from air and water under atmospheric conditions.Experimental results showed that the system with a dualloop design performs well in terms of energy costs and production rates.Optimal operational parameters for the system were determined through experimentation,resulting in an energy cost of 13.9 MJ mol^(-1)and an energy efficiency of 16 g kWh^(-1)for NO_(3)^(-)production,respectively.Moreover,the concentration of exhausted NO_(x)was below the emission standards.Soilless lettuce cultivation experiments demonstrated that NO_(x)^(-)produced by the PNF system could serve as liquid nitrate nitrogen fertilizer.Overall,our work demonstrates the potential of the developed PNF system for on-site application in the production of green-leaf vegetables.

关键词： plasma nitrogen fixation gliding arc soilless cultivation lettuce

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