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An improved interval model updating method via adaptive Kriging models

Applied Mathematics and Mechanics(English Edition) 2024年第3期45卷 497-514页

作者： Sha WEI Yifeng CHEN Hu DING Liqun CHEN Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Frontier Science Center of MechanoinformaticsShanghai Institute of Applied Mathematics and MechanicsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200072China Shanghai Institute of Aircraft Mechanics and Control Shanghai 200092China

Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample ***,the surrogate model in IMU methods mostly adopts the one-time construction *** makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU ***,an improved IMU method via the adaptive Kriging models is *** method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey *** optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is *** the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity *** sampling is then performed in key subspaces based on the maximum mean square error(MMSE)*** interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy *** effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical *** results show that the updated results of the interval model are in good agreement with the experimental results.

关键词： interval model updating(IMU) non-probabilistic uncertainty adaptive Kriging model surrogate model grey number

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A Current Proportional-Differential Feedforward-Based Bidirectional Seamless Fast Dynamic Response control for Dual-Active-Bridge Converters 2

A Current Proportional-Differential Feedforward-Based Bidire...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Cheng, Shijie Wang, Wei Chen, Alian School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350313765

Fast load dynamic response is the main requirement for a high-performance dual-active-bridge (DAB) DC/DC converter. Conventional load current feedforward (LCFF) strategy or its improved variants have been shown to improve dynamic response significantly. However, in these strategies, the control delay existing in the DAB control loop is neglected, and the dynamic response is not truly optimal. To fill this gap, this paper establishes the mathematical model representing the relationship between the transient disturbance of load current and the output voltage to analyze the effects caused by the control delay, based on which a current proportional-differential feedforward-based (CPDF) strategy is proposed to compensate the control delay in the DAB converter. Faster output voltage recovery after sampling the CPDF strategy during load transients. In addition, the CPDF strategy does not need any hardware modification compared with LCFF-based strategies. Finally, both simulations and experiments have verified the practicality and effectiveness of the proposed strategy. © 2023 IEEE.

关键词： control delay current feedforward compensation dual-active-bridge (DAB) dynamic response voltage control

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Active Sampling Planning by Attention-Based Deep Neural Network for Environmental Field Mapping 5

Active Sampling Planning by Attention-Based Deep Neural Netw...

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5th International Conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2023

作者： Wang, Kun Cheng, Qingyuan Lai, Xiaohang Li, Teng School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350357950

Regarding the problem of environmental field reconstruction, a method is proposed to establish the optimal observation position of the environmental field using a random process and complete the online planning of the optimal observation position through deep learning technology. First, this chapter uses a random process method to construct an environmental field model and describes the environmental object as a Gaussian Markov process. For the variable spatial field random process model, the information gain evaluation mechanism is used to define the sampling point with the most information in the field as the approximate optimal observation position, and the global optimal observation point is generated. Subsequently, this chapter proposes a high-precision fitting representation and real-time calculation framework based on a deep attention network, constructs a deep neural network with complex nonlinear representation learning ability, learns the relationship between the covariance function corresponding to the Gaussian random field and the optimal information observation point, simulates the global optimal observation position generated by the random process environment model, solves the real-time calculation of the global optimal position, and realizes the online representation and planning of the spatial field observation position. © 2023 IEEE.

关键词： Active sampling Deep learning Environmental mapping Robotic sensing

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Second-Order Sliding Mode control Strategy With Enhanced DC-link Voltage Stability for PWM Rectifier 11

Second-Order Sliding Mode Control Strategy With Enhanced DC-...

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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Shen, Yuqi Ren, Qicai Chen, Alian Shandong University School of Control Science and Engineering Jinan China

ISBN: (纸本)9788957083505

A PWM rectifier is essential to maintain the DC-bus voltage stable in a power router. However, overshoot or drop of DC-link voltage will be caused by load changing or part power fluctuation. Therefore, a novel variable structure sliding mode control (SMC) strategy based on the super-twisting algorithm (STA) is proposed, improving the rectifier's robustness and fast response capability. The influence of voltage error is fully considered in the design of the DC-link voltage control loop. The DC-link voltage is tracked by using STA, which tremendously suppresses voltage fluctuation. The current inner loop is designed based on the second-order sliding mode (SOSM) algorithm to further accelerate the current grid response. The SMC strategy has a faster voltage and current tracking speed than the traditional PI control. In addition, the stability of DC-link voltage is significantly enhanced. Finally, the OPAL-RT digital experimental platform verifies the proposed control strategy's effectiveness. © 2023 The Korean Institute of Power Electronics.

关键词： Sliding mode control

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An Online Fault Diagnosis Method Based on Multiscale Permutation Entropy for Lithium-ion Battery Pack 7

An Online Fault Diagnosis Method Based on Multiscale Permuta...

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7th CAA International Conference on Vehicular control and Intelligence, CVCI 2023

作者： Ma, Lubin Pang, Qitian Li, Yichao Liu, Xuefeng Duan, Bin Zhang, Chenghui School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350340488

Efficient and accurate battery fault diagnosis is the foundation and prerequisite for the safe and stable development of electric vehicles. The vast majority of thermal runaway in electric vehicles is caused by a short circuit fault in the battery, which can lead to fire and explosion. Therefore, it is crucial to detect short circuit fault quickly and accurately. But common fault diagnosis methods are difficult to detect battery abnormality in the early stages. In this paper, an online fault diagnosis method of lithium-ion batteries based on multiscale permutation entropy (MPE) is proposed, which can effectively handle the voltage characterization information at the early stage of fault. The value of MPE is processed to derive the abnormality coefficient (AC), and the minor fault can be diagnosed by comparing the AC of the battery. Compared with the traditional permutation entropy (PE) algorithm, the MPE algorithm can detect the occurrence of faults at multiple scales and can be applied in progressive fault diagnosis. The experiment results indicate that the proposed MPE method can effectively detect short circuit fault in the early stages with high accuracy and strong robustness. © 2023 IEEE.

关键词： Electric vehicles Fault diagnosis Lithium-ion batteries Multiscale permutation entropy (MPE) Short circuit fault

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Developer Cooperation Relationship and Attribute Similarity Based Community Detection in Software Ecosystem

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Chinese Journal of Electronics 2023年第1期32卷 39-50页

作者： SHEN Xin DU Junwei GONG Dunwei YAO Xiangjuan School of Information and Control Engineering China University of Mining and Technology School of Information Science and Technology Qingdao University of Science and Technology School of Mathematics China University of Mining and Technology

A software ecosystem(SECO) can be described as a special complex network. Previous complex networks in an SECO have limitations in accurately reflecting the similarity between each pair of nodes. The community structure is critical towards understanding the network topology and function. Many scholars tend to adopt evolutionary optimization methods for community detection. The information adopted in previous optimization models for community detection is incomprehensive and cannot be directly applied to the problem of community detection in an SECO. Based on this, a complex network in SECOs is first built. In the network, the cooperation intensity between developers is accurately calculated, and the attribute contained by each developer is considered. A multi-objective optimization model is formulated. A community detection algorithm based on NSGA-II is employed to solve the above model. Experimental results demonstrate that the proposed method of calculating the developer cooperation intensity and our model are advantageous.

关键词： Biological system modeling Ecosystems Optimization methods Complex networks Software Detection algorithms

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Dirac method for nonlinear and non-homogenous boundary value problems of plates

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Applied Mathematics and Mechanics(English Edition) 2024年第1期45卷 15-38页

作者： Xiaoye MAO Jiabin WU Junning ZHANG Hu DING Liqun CHEN Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Frontier Science Center of MechanoinformaticsShanghai Institute of Applied Mathematics and MechanicsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200444China Shanghai Institute of Aircraft Mechanics and Control Shanghai 200092China

The boundary value problem plays a crucial role in the analytical investigation of continuum dynamics. In this paper, an analytical method based on the Dirac operator to solve the nonlinear and non-homogeneous boundary value problem of rectangular plates is proposed. The key concept behind this method is to transform the nonlinear or non-homogeneous part on the boundary into a lateral force within the governing function by the Dirac operator, which linearizes and homogenizes the original boundary, allowing one to employ the modal superposition method for obtaining solutions to reconstructive governing equations. Once projected into the modal space, the harmonic balance method(HBM) is utilized to solve coupled ordinary differential equations(ODEs)of truncated systems with nonlinearity. To validate the convergence and accuracy of the proposed Dirac method, the results of typical examples, involving nonlinearly restricted boundaries, moment excitation, and displacement excitation, are compared with those of the differential quadrature element method(DQEM). The results demonstrate that when dealing with nonlinear boundaries, the Dirac method exhibits more excellent accuracy and convergence compared with the DQEM. However, when facing displacement excitation, there exist some discrepancies between the proposed approach and simulations;nevertheless, the proposed method still accurately predicts resonant frequencies while being uniquely capable of handling nonuniform displacement excitations. Overall, this methodology offers a convenient way for addressing nonlinear and non-homogenous plate boundaries.

关键词： rectangular plate Dirac operator nonlinear boundary time-dependent boundary boundary value problem

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A Maximum Principle for Forward-Backward Stochastic control Problem Under Partial Information 42

A Maximum Principle for Forward-Backward Stochastic Control ...

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42nd Chinese control Conference, CCC 2023

作者： Guo, Zhongbin School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9789887581543

We study the stochastic optimal control problem for forward-backward stochastic systems with correlated state and observation noises. In our problem, we consider a more general situation. Firstly, the observation process depends explicitly on control. Secondly, the coefficients of SDE depend on the expectation of state. Using Girsanov's theorem and spike variation, we derive a maximum principle that is described by conditional mathematical expectation. The adjoint equation is a type of mean-field forward-backward stochastic differential equations and contains additional equations which are not necessary in the case of full information. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Maximum principle

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Impact of coking plant to heavy metal characteristics in groundwater of surrounding areas:Spatial distribution,source apportionment and risk assessments

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Journal of Environmental sciences 2025年第3期149卷 688-698页

作者： Congqing Wang Wanjun Wang ChaoWang Shixing Ren Yingjun Wu Meicheng Wen Guiying Li Taicheng An Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control Guangdong Hong Kong-Macao Joint Laboratory for Contaminants Exposure and HealthInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Guangzhou Key Laboratory Environmental Catalysis and Pollution Control Key Laboratory of City Cluster Environmental Safety and Green developmentSchool of Environmental Science and EngineeringGuangdong University of TechnologyGuangzhou 510006China

Coking industry is a potential source of heavy metals(HMs)***,its impacts to the groundwater of surrounding residential areas have not been well *** study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking *** HMs including Fe,Zn,Mo,As,Cu,Ni,Cr,Pb and Cd were *** average concentration of total HMswas higher in the nearby area(244.27μg/L)than that of remote area away the coking plant(89.15μg/L).The spatial distribution of pollution indices including heavy metal pollution index(HPI),Nemerow index(NI)and contamination degree(CD),all demonstrated higher values at the nearby residential areas,suggesting coking activity could significantly impact the HMs distribution *** sources of HMs were identified by Positive Matrix Factorization(PMF)model,which indicated coal washing and coking emission were the dominant sources,accounted for 40.4%,and 31.0%,*** ingestionwas found to be the dominant exposure pathway with higher exposure dose to children than *** quotient(HQ)values were below 1.0,suggesting negligible non-carcinogenic health risks,while potential carcinogenic risks were from Pb and Ni with cancer risk(CR)values>10−*** Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive *** study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater,thus facilitating the implement of HMs regulation in coking industries.

关键词： Coking industry Heavy metal Groundwater Spatial distribution Source apportionment Monte Carlo simulation

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Event-triggered stochastic MPC for linear systems with additive stochastic disturbances 18

Event-triggered stochastic MPC for linear systems with addit...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Gu, Chenxi Wang, Xinli Yi, Anning Wang, Lei Shandong University School of Control Science and Engineering Jinan China

ISBN: (纸本)9798350312201

This paper takes discrete-time linear systems subject to uncertainties into consideration and constructs an event-triggered stochastic model predictive controller to minimize the objective function that has a quadratic chance constraint over an infinite horizon. This paper derives an event trigger condition use the input-to-state stability (ISS) framework to save the computational resources. Moreover, the chance constraint is formulated as the sum of the probability of a constrain violation with weights that decreases exponentially over time. An event- triggered stochastic model predictive control optimization problem is established using Chebyshev's inequality and the recursive feasibility is guaranteed by using the online constraint-tightening technique. We demonstrate these results through a numerical simulation of an HVAC system. © 2023 IEEE.

关键词： Stochastic models

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