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Fixed-time stabilization of discontinuous spatiotemporal neural networks with time-varying coefficients via aperiodically switching control

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Science China(Information Sciences) 2023年第5期66卷 182-195页

作者： Xiaofang HU Leimin WANG Chuan-Ke ZHANG Xiongbo WAN Yong HE 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

This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.

关键词： spatiotemporal neural networks discontinuous activations time-varying coefficients fixed-time stabilization aperiodically switching control

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Charge transporting materials for perovskite solar cells

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Rare Metals 2021年第10期40卷 2690-2711页

作者： Ting Ji Ying-Kui Wang Lin Feng Guo-Hui Li Wen-Yan Wang Zhan-Feng Li Yu-Ying Hao Yan-Xia Cui College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan University of TechnologyTaiyuan 030024China

Perovskite solar cells(PSCs) have made great progress since 2009 and become the focus of current research. As an important part of PSCs, charge transporting materials play an important role in the performance of the devices. In this review, we introduce the evolution of electron and hole transporting materials in PSCs in recent years and summarize some typical charge transporting materials and their applications in PSCs. For electron transporting materials, metal oxides(TiO_(2), SnO_(2) and ZnO) and organic materials(fullerenes, non-fullerenes and their derivatives)are the most widely used materials in PSCs. For hole transporting materials, small molecule spiro-OMeTAD(2,2’,7,7’-Tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9’-spirobifluorene), polymer PEDOT:PSS(poly(3,4-ethylenedioxythiophene): polystyrene sulfonate), PTAA(poly-[bi(4-phenyl)](2,4,3-trimethylphenyla-mine)), P3 HT(poly(3-hexythiophene)) and inorganic materials(NiOx, CuSCN, CuO) are adopted in PSCs. Finally, different types of charge transporting materials are summarized and their future development is prospected.

关键词： Perovskite Solar cells Electron transporting materials Hole transporting materials

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A Hybrid Data-Driven Granular Model for Battery Remaining Useful Life Prediction

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Jing, TaiLong Du, Sheng Wang, Cong Wu, Chao Pedrycz, Witold Sharaf, Mohamed Li, ZhiWu Luoyang Institute of Science and Technology School of Electrical Engineering and Automation Luoyang471023 China China University of Geosciences School of Automation 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 Xi’an710072 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland King Saud University College of Engineering Department of Industrial Engineering Riyadh11421 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau China

Accurate and meaningful prediction of the remaining useful life (RUL) of lithium-ion batteries (LIBs) provides a significant guide for the maintenance and management of these LIBs. A singular numerical predictive result by numerous conventional models is insufficient to furnish decision-makers with comprehensive or nuanced insights. To address this issue, predictive RUL results in the form of information granules are essential. In this study, a hybrid data-driven granular model is established for battery RUL prediction with granular (interval-based) quantification for LIBs. This granular model is designed and formulated in a way that it produces comprehensive prediction outcomes realized as information granules, which are expressed in a more descriptive and comprehensive manner. Thus, the resulting information granules can effectively reflect and communicate the confidence associated with the predictions. The granular model is realized in two steps: 1) probabilistic prediction results are produced by a hybrid numeric predictive model and 2) a comprehensive granulation of the probabilistic results is achieved under the principle of information granularity. The granular predictive results are holistically evaluated and optimized by the two associated criteria of granularity (coverage and specificity). This transformation of information granules provides an intuitive and interpretable display for battery maintenance and safe work. The proposed granular model is verified by using an open-access LIBs dataset, and the experimental results demonstrate that the proposed granular model outperforms other comparative methods. © 2025 IEEE. All rights reserved.

关键词： Prediction models

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Extended Dissipativity Analysis for Delayed Markovian Jump Neural Networks via a Delay-Interval-Adjustable-Based Lyapunov–Krasovskii Functional

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IEEE Transactions on Cybernetics 2025年 PP卷 PP页

作者： Chang, Xu-Kang He, Yong China University of Geosciences School of Automation 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

The issue of extended dissipativity analysis (EDA) for delayed Markovian jump neural networks (MJNNs) is investigated in this article. First, a delay-interval-adjustable-based Lyapunov–Krasovskii functional (LKF) is proposed, in which the delay interval is adjusted by a tunable parameter to obtain an optimal extended dissipativity result, offering a new idea to enhance the consideration of delay information. Furthermore, to take into account more effective information, the LKF is augmented with both single and quadratic integral variables. Accordingly, the LKF derivative becomes a higher-order term of the time-varying delay. To solve this nonlinear problem, a variable-augmented-based free-weighting-matrices approach is employed to transform the nonlinear term into a linear form and provides more freedom in obtaining enhanced EDA results. Then, two novel extended dissipativity criteria of delayed MJNNs are derived. Meanwhile, to show the general applicability of the proposed methods, the derived criteria are applied to the EDA and stability analysis for delayed neural networks (NNs). Lastly, the merits and effectiveness of the proposed techniques are demonstrated through three numerical examples and a real-world application of a quadruple-tank process system. Additionally, the proposed methods can be effectively applied to the practical fields of power system stability control, robot motion control, and image processing, while reducing the conservatism of system performance results. © 2013 IEEE.

关键词： Motion analysis

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Flow control for a Two-Stage Proportional Valve with Hydraulic Position Feedback

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Chinese Journal of Mechanical Engineering 2020年第6期33卷 64-76页

作者： He Wang Xiaohu Wang Jiahai Huang Long Quan Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan030024China Shanxi Transportation Technology Research&Development Co. LtdTaiyuan030024China

The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor ***,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load *** flow fluctuation severely restricts the application of the Valvistor *** this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow *** mathematical model of this valve is established and *** proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control *** feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main *** results show that inference with BPNN can obtain the flow data fast and *** the flow control method,the flow can keep at the set point when the pressure differential across the main orifice *** flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow *** the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes *** performances of hysteresis,linearity and bandwidth are in a high *** linear mathematical model can be verified and the assumptions in the system modeling is reasonable.

关键词： Flow control Proportional valve Hydraulic position feedback Back-propagation neural network

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method

Path Planning for Distribution Network Robots with Adaptive ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Baichao Zhang Xin Chen Jinge Chen Jinbin Li Xiaokai Wang Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan P. R. China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan P. R. China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. Simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications.

关键词： Electric potential Adaptation models Force Distribution networks Simulated annealing Manipulators Path planning Planning Collision avoidance Robots

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Multimodal Emotion Recognition Based on Multi-Scale Facial Features and Cross-Modal Attention

Multimodal Emotion Recognition Based on Multi-Scale Facial F...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Bao, Chengao Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Tokyo Institute of Technology Yokohama226-8502 Japan Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798331521950

A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branch ViT architecture by using classification tokens in each branch to interact with picture embeddings in the other branch, which facilitates effective interactions between different scales of information. Subsequently, audio features are extracted using ResNet18 network. The cross-modal attention mechanism is used to obtain the weight matrices between different modal features, making full use of inter-modal correlation and effectively fusing visual and audio features for more accurate emotion recognition. Two datasets are used for the experiments: eNTERFACE'05 and REDVESS dataset. The experimental results show that the accuracy of the proposed method on the eNTERFACE'05 and REDVESS datasets is 85.42% and 83.84% respectively, which proves the effectiveness of the proposed method. © 2025 IEEE.

关键词： Modal analysis

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Multi-objective Evolutionary Algorithm Based Graph Neural Network Architecture Search

Multi-objective Evolutionary Algorithm Based Graph Neural Ne...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： He, Lianyi Liu, Xiaobo Xiang, Hongbo Wang, Guangjun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences Wuhan430074 China

ISBN: (纸本)9789819647521

Graph Neural Networks (GNN) has become a powerful graph data processing method, which has been widely used in node classification, link prediction, and other graph analysis tasks. Due to the diversity and complexity of graph structures and information propagation, as well as the handling of heterogeneous graphs, etc., the design of GNNs presents many challenges. The existing methods have high classification accuracy, but their structures are very complex. In this paper, a graph neural network architecture search framework named MO-GNN, which is based on multi-objective evolutionary algorithm is proposed. Furthermore, a weight sharing strategy MO-GNN-WS is proposed to reduce the resource consumption caused by weight training of different architectures. To verify the performance of the proposed algorithm, experiments on four popular graph datasets are used for transduction and induction tasks. The experimental results show that the MO-GNN-WS algorithm outperforms the most advanced neural network architecture search methods in terms of classification accuracy and resource consumption. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data Sharing

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Simplified outlier detection for improving the robustness of a fuzzy model

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Science China(Information Sciences) 2020年第4期63卷 218-220页

作者： Yali JIN Weihua CAO Min WU Yan YUAN School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,Fuzzy models have been widely employed in various fields, such as complex industrial process modeling, classification, function approximation, and time series prediction. Extracting fuzzy rules is very important as they determine the capabilities of the fuzzy model. In recent years, data-based methods such as fuzzy clustering, genetic algorithm, and neural networks [1–3], have been pro-

关键词： Simplified outlier detection for improving the robustness of a fuzzy model Gaussian

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Periodic and chaotic oscillations in mutual-coupled mid-infrared quantum cascade lasers

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Chinese Physics B 2022年第10期31卷 352-361页

作者： Zhi-Wei Jia Li Li Yi-Yan Guo An-Bang Wang Hong Han Jin-Chuan Zhang Pu Li Shen-Qiang Zhai Feng-Qi Liu Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Semiconductor Materials Science Beijing Key Laboratory of Low Dimensional Semiconductor Materials and DevicesInstitute of SemiconductorsChinese Academy of SciencesBeijing 100083China

Dynamic states in mutual-coupled mid-infrared quantum cascade lasers(QCLs) were numerically investigated in the parameter space of injection strength and detuning frequency based on the Lang-Kobayashi equations model. Three types of period-one states were found, with different periods of injection time delay τ_(inj), 2τ_(inj), and reciprocal of the detuning frequency. Besides, square-wave, quasi-period, pulse-burst and chaotic oscillations were also observed. It is concluded that external-cavity periodic dynamics and optical modes beating are the mainly periodic dynamics. The interaction of the two periodic dynamics and the high-frequency dynamics stimulated by strong injection induces the dynamic states *** work helps to understand the dynamic behaviors in QCLs and shows a new way to mid-infrared wide-band chaotic laser.

关键词： periodic oscillations chaotic oscillations mutual-coupled quantum cascade lasers

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