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Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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Non-contact video-based vital signs continuous monitor for uncontrained conscious rodents

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IEEE Sensors Journal 2025年第10期25卷 16628-16639页

作者： He, Yuke Gao, Tong Lv, Yong Zhang, Jingjing China University of Geoscienceis Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China

Animal experiments should minimize pain and discomfort and maximize animal welfare to satisfy the experimental animal 3R principle. The quality of vital signs monitor results collected from conscious and stress-free rodents is superior, ensuring experimental data's reliability, accuracy, and scientificity. This work proposes a non-contact video-based vital signs continuous monitoring method for uncontrained conscious rodents. Firstly, rodents are tracked using keypoint detection, and Regions of Interest (ROI) on the rodents are selected based on signal-to-noise ratio (SNR) distribution of vital signs. Secondly, corner motion within the ROI region is tracked to synthesize skin pulsations, from which respiratory signals are extracted. Finally, a method is proposed to eliminate the influence of respiratory harmonics, thereby removing respiratory interference and extracting the heart rate. Four rats and four mice were used to measure the performance of the proposed method. This work is the first to use a camera to continuously monitor the heart rate of unrestrained and conscious rodents. Compared with the ground truth (semi-implantable electrocardiogram), the relative heart rate (HR) error was 1.86 ± 0.82% and 1.20 ± 0.33% for rats and mice, respectively. This method is used for uncontrained conscious rodents and has high applicability, allowing it to be used in various experimental environments and conditions. At the same time, this work contributes to the development of new methods for continuously and objectively evaluating animal welfare, thereby promoting the development of modern biomedical and ethical research. © 2001-2012 IEEE.

关键词： Invertebrates

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min 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

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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Consensus of discrete-time heterogeneous multi-agent systems in noisy environments without velocity transmission

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ASIAN JOURNAL OF control 2025年第0期

作者： Chen, Jiali Zong, Xiaofeng Hou, Xuping Wang, Zi-Xuan China Univ Geosci Sch Automat Wuhan Peoples R China Hubei Key Lab Adv Control & Intelligent Automation Wuhan Peoples R China Minist Educ Engn Res Ctr Intelligent Technol GeoExplorat Wuhan Peoples R China

This paper investigates consensus control of discrete-time heterogeneous multi-agent systems with multiplicative noise. As the frequent absence of velocity sensors in real industrial environments, a control protocol is developed using absolute velocity and relative position measurement information. Then, the consensus control issue is reformulated as the stability issue of stochastic difference equations. By choosing an appropriate Lyapunov function, the above stability issue is studied, and the sufficient conditions for leader-free and leader-following discrete-time heterogeneous multi-agent systems to achieve both mean-square and almost-sure consensus are derived, respectively. Finally, numerical simulations are provided to validate the effectiveness of the main results.

关键词： consensus discrete-time heterogeneous multi-agent systems leader-following leader-free multiplicative noise

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Congruent-transformation-based stability criterion of T-S fuzzy systems with time-varying delay via the generalized line-integral Lyapunov function

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IEEE Transactions on automation Science and Engineering 2025年 22卷 14669-14678页

作者： Liu, Zhou-Zhou Jin, Li He, Yong China University of Geosciences School of Automation Wuhan430074 China China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

This paper is concerned with the stability analysis of Takagi-Sugeno (T-S) fuzzy systems with time-varying delays. First, by constructing a generalized line-integral Lyapunov function (GLILF), applying the free-matrix-based inequality and the delay-derivative-dependent free-weighting-matrices method, a basic stability criterion is derived. Besides, the structure of the matrices in the stability criterion is reconstructed through congruent transformation, and an improved stability criterion is derived accordingly. To clarify the advancement of the proposed method, a stability condition is given without the GLILF. Finally, two numerical examples and a practical example are applied to show the advancement and merits of the presented method. © 2004-2012 IEEE.

关键词： Lyapunov functions

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A matrix-separation-based integral inequality for aperiodic sampled-data synchronization of delayed neural networks considering communication delay

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APPLIED MATHEMATICS AND COMPUTATION 2025年 486卷

作者： Wang, H. -Z Shangguan, X. -C Xiong, D. An, Y. -H Jin, L. China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automation Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China

This paper achieves the synchronization of delayed neural networks (DNNs) considering aperiodic sampled-data control and communication delay. First of all, based on the master- slave DNNs with aperiodic sampling synchronization controller, a synchronization error system is constructed. Then, an augmented functional containing both the error state and its derivative is constructed. Compared with the existing researches, the augmented functional introduces more cross information of error states to the criterion. Next, an integral inequality based on the separation of internal integral variable and matrix is developed. Compared to the inequalities that treat the internal variable and the matrix as unified ones, the developed inequality provides a tighter estimate of the derivative of the augmented functional. On this basis, a criterion with less conservative is developed for the aperiodic sampled-data synchronization of DNNs considering communication delay. Finally, to indicate the superiority of the developed method on improving the acceptable sampling upper bound of synchronization, three numerical examples are provided.

关键词： Delayed neural networks Master-slave synchronization Aperiodic sampled-data control Matrix-separation-based integral inequality

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Unit load prediction method based on weighted just-in-time learning with spatio-temporal characteristics for gas boiler power generation process

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control ENGINEERING PRACTICE 2025年 160卷

作者： Xu, Yan Wu, Min Hu, Jie Du, Sheng Zhang, Wen Peng, Fusheng Li, Huihang Song, Wenshuo China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automation Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China

Load management of gas boiler generator units in metallurgical captive power plants heavily relies on operators' coordination and scheduling. The operating load fluctuates frequently due to varying electricity demands across production processes and its sensitivity to multiple operational parameters. To accurately predict unit load, promptly reflect load changes, and ensure stable operation, we propose a unit load prediction model utilizing a weighted just-in-time learning algorithm with consideration of key parameter spatio-temporal characteristics (WJITL-ST) and a long short-term memory network with temporal pattern attention (TPA-LSTM) mechanism. First, we thoroughly analyze the process mechanism and use the maximum information coefficient to identify and select the variables most relevant to unit load as model inputs. Next, the WJITL-ST method, based on data segment retrieval, selects historical data most similar to the retrieved segments for online local modeling. The TPA-LSTM algorithm is then used to model and predict unit load. Finally, experiments using actual production data from a 150MW gas boiler generator unit in a metallurgical captive power plant show that the proposed method achieves higher prediction accuracy, and demonstrates superior performance under fluctuating operating conditions.

关键词： Power generation process Unit load prediction Weighted just-in-time learning Attention mechanism

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Event denoising for dynamic vision sensor using residual graph neural network with density-based spatial clustering☆

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NEUROCOMPUTING 2025年 636卷

作者： Feng, Weibin Wang, Xiaoping Zhan, Xin Huang, Hongzhi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Brain inspired Intelligent Syst Wuhan 430074 Peoples R China

The bio-inspired emerging dynamic vision sensor (DVS), characterized by its exceptional high temporal resolution and immediate response, possesses an innate advantage in capturing rapidly changing scenes. Nevertheless, it is also susceptible to severe noise interference, especially in challenging conditions like low illumination and high exposure. Notably, the existing noise processing approaches tend to oversimplify data into 2-dimensional (2D) patterns, disregarding the sparse and irregular crucial event structure information that the DVS intrinsically provides via its asynchronous output. Aiming at these problems, we propose a residual graph neural network (RGNN) framework based on density spatial clustering for event denoising, called DBRGNN. Leveraging the temporal window rule, we extract non-overlapping event segments from the DVS event stream and adopt a density-based spatial clustering algorithm to obtain event groups with spatial correlations. To fully exploit the inherent sparsity and plentiful spatiotemporal information of the raw event stream, we transform each event group as compact graph representations via directed edges and feed them into a graph coding module composed of a series of graph convolutional and pooling layers to learn robust geometric features from event sequences. Importantly, our approach effectively reduces noise levels without compromising the spatial structure and temporal coherence of spike events. Compared with other baseline methods, our DBRGNN achieves competitive performance by quantitative and qualitative evaluations on publicly available datasets under varying lighting conditions and noise ratios.

关键词： DVS Event denoising Temporal window Density-based clustering Graph learning for visual processing

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Finite-Time Consensus of Second-Order Multiagent Systems With Input Saturation via Hybrid Sliding-Mode control

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IEEE Transactions on automation Science and Engineering 2025年 22卷 14623-14632页

作者： Jiang, Xiaowei Jiao, Ranran Li, Bo Zhang, Xianhe Yan, Huaicheng China University of Geosciences School of Automation Wuhan430079 China Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Anhui University of Finance and Economics School of Finance Bengbu233030 China Hubei Normal University School of Electrical Engineering and Automation Huangshi435002 China Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China

This paper addresses the finite-time consensus (FTC) issue for second-order multi-agent systems (MASs) with nonlinear disturbances. To tackle the challenges posed by increasingly complex communication environments, an innovative integral sliding-mode surface is designed using event-triggered control. Furthermore, the study explores communication constraints between the leader and followers, employing impulsive control to facilitate communication only at specific intervals. A novel hybrid integral sliding-mode control protocol is advanced for the second-order MASs, which effectively eliminates the "Zeno phenomenon" and notably reduces both communication frequency and energy consumption, thereby enhancing overall communication efficiency. Ultimately, the efficacy of the put forward protocol is verified through simulation examples including comparison experiment. © 2004-2012 IEEE.

关键词： Protocols Sliding mode control Event detection Multi-agent systems Costs Training Topology Switches Sufficient conditions Stability analysis

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A radial visualization method based on knee point information for many-objective optimization

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APPLIED SOFT COMPUTING 2025年 175卷

作者： Li, Gui Xiao, Renbin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Inst Artificial Intelligence Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

Numerous high-dimensional solutions for many-objective optimization problems (MaOPs) usually impose a high cognitive burden on decision makers (DMs). Pareto front (PF) of MaOPs can express the problem characteristics, and then provide prior knowledge for solving the MaOPs. However, the existing high-dimensional visualization methods usually do not establish the relationship between PF information and decision making. Therefore, a novel radial visualization (RadViz) method called KRadViz that incorporates knee point information is proposed to visualize the information of PF shape and aid decision making. The relationship between the optimized performance information and PF shape is established, and the PF shape identification method is constructed. KRadViz is constructed by combining the optimization performance and PF shape. Three preferred solution selection methods are proposed to quickly screen out a few preferred solutions in different scenarios. The proposed KRadViz is compared with three high-dimensional visualization methods. The experimental results show that KRadViz can effectively display the high-dimensional PF shape, and give the optimization performance information of different solutions. The selection preferences of the three methods are also analyzed, and the effectiveness of the assisted decision process is verified. For the DTLZ2 and real-world MaOPs, the individual hypervolume (HV) contribution of preferred solutions increased by 9.98 % and 10.95 %, respectively.

关键词： Many-objective optimization High-dimensional visualization Knee points Preferred information RadViz

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