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Dynamic Balance control Based on an Adaptive Gain-scheduled Backstepping Scheme for Power-line Inspection Robots

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 198-208页

作者： Songyi Dian Lin Chen Son Hoang Ming Pu Junyong Liu the School of Electrical engineering and information Sichuan University the college of control engineering Chengdu University of Information Technology

This paper presents an adaptive gain-scheduled backstepping control(AGSBC) scheme for the balance control of an underactuated mechanical power-line inspection(PLI) robotic system with two degrees of freedom and a single control input.First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points,an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control(GSBC) scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.

关键词： Adaptive backstepping balance control gain-scheduled inspection robot power line

Intelligent Orchestrating of IoT Microservices Based on Reinforcement Learning

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Chinese Journal of Electronics 2022年第5期31卷 930-937页

作者： WU Yuqin SHEN Congqi CHEN Shuhan WU Chunming LI Shunbin WEI Ruan college of Computer Science and Technology Zhejiang University college of information and Electrical engineering Ningde Normal University Zhejiang Lab college of control Science and engineering Zhejiang University

With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices in IoT is explored. A type of reinforcement learning(RL) algorithm called TD3 is used to generate the optimal choreography policy under the framework of a softwaredefined network. The optimal policy is gradually reached during the learning procedure to achieve the goal, despite the dynamic characteristics of the network environment. The simulation results show that compared with other methods, the TD3 algorithm converges faster after a certain number of iterations, and it performs better than other non-RL algorithms by obtaining the highest reward. The TD3 algorithm can effciently adjust the traffic transmission path and provide qualified IoT services.

关键词： Internet of things Microservice Traffc scheduling Reinforcement learning

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1079-1088页

作者： Xue Chen Yanjiang Wang college of information and control engineering China University of Petroleum (East China)

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

关键词：网络功能连通性自动化技术发展现状

基于盲源分离与文丘里流量计的气液两相段塞流测量(英文)

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Chinese Journal of Chemical engineering 2015年第9期23卷 1447-1452页

作者：王微微梁霄张明柱 college of information and control engineering China University of Petroleum

We propose a novel flow measurement method for gas–liquid two-phase slug flow by using the blind source separation technique. The flow measurement model is established based on the fluctuation characteristics of differential pressure(DP) signals measured from a Venturi meter. It is demonstrated that DP signals of two-phase flow are a linear mixture of DP signals of single phase fluids. The measurement model is a combination of throttle relationship and blind source separation model. In addition, we estimate the mixture matrix using the independent component analysis(ICA) technique. The mixture matrix could be described using the variances of two DP signals acquired from two Venturi meters. The validity of the proposed model was tested in the gas–liquid twophase flow loop facility. Experimental results showed that for most slug flow the relative error is within 10%.We also find that the mixture matrix is beneficial to investigate the flow mechanism of gas–liquid two-phase flow.

关键词：盲源分离技术气液两相流文丘里管测量方法段塞流文丘里流量计测量信号混合矩阵

一种基于含噪时序结构独立元分析的过程监控方法(英文)

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Chinese Journal of Chemical engineering 2015年第1期23卷 162-172页

作者：蔡连芳田学民 college of information and control engineering China University of Petroleum

Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the adverse effects of the measurement noises. In this paper, a new process monitoring approach based on noisy time structure ICA(Noisy TSICA) is proposed to solve such problem. A Noisy TSICA algorithm which can consider the measurement noises explicitly is firstly developed to estimate the mixing matrix and extract the independent components(ICs). Subsequently, a monitoring statistic is built to detect process faults on the basis of the recursive kurtosis estimations of the dominant ICs. Lastly, a contribution plot for the monitoring statistic is constructed to identify the fault variables based on the sensitivity analysis. Simulation studies on the continuous stirred tank reactor system demonstrate that the proposed Noisy TSICA-based monitoring method outperforms the conventional Fast ICA-based monitoring method.

关键词：快速独立分量分析监控方法时间结构测量噪声监测方法监测统计 ica算法敏感性分析

Supervised Penalty Matrix Decomposition for Tumor Differentially Expressed Genes Selection

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Chinese Journal of Electronics 2018年第4期27卷 845-851页

作者： LIU Jian CHENG Yuhu WANG Xuesong CUI Xiaoluo School of information and control engineering China University of Mining and Technology Department of information engineering Weihai Ocean Vocational College

A reliable and precise recognition of the differentially expressed genes of tumor is crucial to treat the cancer effectively. The small number of differentially expressed genes in a huge gene expression dataset determines the important role of sparse methods, such as Penalty matrix decomposition(PMD), among the feature selection methods. The sparse methods always have the drawback: they do not take advantage of known class labels of gene expression data. A novel supervised-sparse method named as Supervised PMD(SPMD) is proposed by adding the class information into PMD via the total scatter matrix. The brief idea of our method used to select the differentially expressed genes is given as follows.The total scatter matrix is obtained according to the gene expression data with class label. The obtained total scatter matrix is decomposed by PMD to acquire the sparse vectors. The non-zero items in sparse vectors are selected as the differentially expressed genes. The Gene ontology(GO) enrichment of functional annotation of the selected genes is detected by Topp Fun. Experiments on synthetic data and two real tumor gene expression datasets show that the proposed SPMD is quite promising to select the differentially expressed genes.

关键词： Tumor gene expression data Differentially expressed genes Supervised methods Scatter matrix Penalized matrix decomposition(PMD)

Thermal time-constant spectrum extraction method in AlGaN/GaN HEMTs

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Journal of Semiconductors 2015年第8期36卷 88-93页

作者：杨军伟冯士维史冬阳春辉 college of Electronic information & control engineering Beijing University of Technology

The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitting algorithm, called locally weighted scatterplot smoothing （LOWESS）. The thermal time-constant spectrum is extracted to analyze the physical structure of the heat-conduction path in A1GaN/GaN HEMTs. The thermal time- constant spectra extracted using the LOWESS algorithm are richer and the RC network obtained is greater compared with those with the traditional denoising method （multi-exponential fitting）. Thus, the analysis of the heat-flow path is more precise. The results show that the LOWESS nonparametric fitting algorithm can remove noise from measured data better than other methods and can retain the subtle variation tendency of the original discrete data. The thermal time-constant spectra extracted using this method can describe the subtle temperature variations in the A1GaN/GaN HEMT active region. This will help researchers to precisely analyze the layer composition of the heat-flow path.

关键词： AlGaN/GaN HEMT LOWESS algorithm exponential fitting time-constant spectrum heat- conduction path

A Metadata Reconstruction Algorithm Based on Heterogeneous Sensor Data for Marine Observations

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Journal of Ocean University of China 2023年第6期22卷 1541-1550页

作者： GUO Shuai SUN Meng MAO Xiaodong college of Science Qingdao University of TechnologyQingdao 266520China college of information and control engineering Qingdao University of TechnologyQingdao 266520China

Vast amounts of heterogeneous data on marine observations have been accumulated due to the rapid development of ocean observation technology.Several state-of-art methods are proposed to manage the emerging Internet of Things(IoT)sensor data.However,the use of an inefficient data management strategy during the data storage process can lead to missing metadata;thus,part of the sensor data cannot be indexed and utilized(i.e.,‘data swamp’).Researchers have focused on optimizing storage procedures to prevent such disasters,but few have attempted to restore the missing metadata.In this study,we propose an AI-based algorithm to reconstruct the metadata of heterogeneous marine data in data swamps to solve the above problems.First,a MapReduce algorithm is proposed to preprocess raw marine data and extract its feature tensors in parallel.Second,load the feature tensors are loaded into a machine learning algorithm and clustering operation is implemented.The similarities between the incoming data and the trained clustering results in terms of clustering results are also calculated.Finally,metadata reconstruction is performed based on existing marine observa-tion data processing results.The experiments are designed using existing datasets obtained from ocean observing systems,thus verifying the effectiveness of the algorithms.The results demonstrate the excellent performance of our proposed algorithm for the metadata recon-struction of heterogenous marine observation data.

关键词： Internet of Things(IoT) sensor data data swamp metadata reconstruction

Analysis on high speed response of a uni-traveling-carrier double hetero-junction phototransistor

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Chinese Physics B 2015年第4期24卷 535-539页

作者：江之韵谢红云张良浩张万荣胡瑞心霍文娟 college of Electronic information and control engineering Beijing University of Technology

In this paper, the positive influence of a uni-traveling-carrier （UTC） structure to ease the contract between the respon- sivity and working speed of the InP-based double hetero-junction phototransistor （DHPT） is illustrated in detail. Different results under electrical bias, optical bias or combined electrical and optical bias are analyzed for an excellent UTC-DHPT performance. The results show that when the UTC-DHPT operates at three-terminal （3T） working mode with combined electrical bias and optical bias in base, it keeps a high optical responsivity of 34.72 A/W and the highest optical transition frequency of 120 GHz. The current gain of the 3T UTC-DHPT under 1.55-μm light illuminations reaches 62 dB. This indicates that the combined base electrical bias and optical bias of 3T UTC-DHPT can make sure that the UTC-DHPT provides high optical current gain and high optical transition frequency simultaneously.

关键词： uni-traveling-carrier double hetero-junction phototransistor optical responsivity optical transition frequency