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Dynamic sequential neighbor processing: A liquid neural network-inspired framework for enhanced graph neural networks

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Information Sciences 2025年 719卷

作者： Kuijie Zhang Shanchen Pang Yuanyuan Zhang Yun Bai Luqi Wang Jerry Chun-Wei Lin State Key Laboratory of Chemical Safety Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software the Qingdao Institute of Software China University of Petroleum Qingdao 266580 China School of information and control engineering Qingdao University of Technology Shandong266520 China Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and IT Devices Silesian University of Technology 44-100 Gliwice Poland

Integrating information from multi-order neighborhoods is a fundamental strategy in Graph Neural Networks (GNNs) for capturing higher-order structural patterns and enhancing the expressive power of node representations. However, most existing GNNs treat neighbors from different orders as unordered sets and integrate them using static or parallel strategies, thus overlooking the sequential and evolving nature of neighborhood expansion. To address this limitation, we propose a novel GNN framework, SL, which integrates Serialized Neighbor Features with Liquid Neural Networks (LNNs) to enable order-aware, dynamic adaptation of neighbor influence. By modeling neighbor features as ordered sequences and leveraging LNNs' internal feedback dynamics, SL adapts feature extraction in real time based on local context and propagation history. This design offers fine-grained control over hierarchical dependencies and allows dynamic modulation of contributions from different neighborhood layers. SL is model-agnostic and can be seamlessly integrated with both classical and state-of-the-art GNNs. Extensive experiments across ten benchmark datasets show that SL consistently improves node classification accuracy and significantly alleviates over-smoothing in deep GNNs. These results highlight that order-aware and dynamically regulated propagation represents a powerful, flexible alternative to traditional multi-order aggregation, enhancing the adaptability and expressiveness of GNNs for complex graph learning tasks.

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Augmented input estimation in multiple maneuvering target tracking

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Journal of systems Engineering and Electronics 2019年第5期30卷 841-851页

作者： HADAEGH Mahmoudreza KHALOOZADEH Hamid BEHESHTI Mohammadtaghi Department of Electrical and Computer Engineering Science and Research BranchIslamic Azad UniversityTehran ***Iran Department of Systems and Control K.N.Toosi University of TechnologyTehran ***Iran Department of Electrical Engineering Control GroupTarbiat Modares UniversityTehran 14115111Iran

This paper presents augmented input estimation(AIE)for multiple maneuvering target ***-target tracking(MTT)is based on two main parts,data association and *** data association(DA),the best observations are assigned to the considered *** real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done *** this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in *** DA,estimation and tracking should be *** in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is *** model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state *** comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.

关键词： multi-target tracking (MTT) Markov chain Monte-Carlodata association (MCMCDA) data association (DA) augmentedinput estimation (AIE)

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Optimal modified PID controller for automatic voltage regulation system

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AIP Conference Proceedings 2022年第1期2415卷

作者： Layla H. Abood Control and systems Engineering Department University of Technology Baghdad Iraq

This paper presents a smart optimization algorithm for tuning a modified structure of PID controller to regulate the terminal voltage of the automatic voltage regulator (AVR), it consists of four parameters proportional, integral and derivative plus second order derivative, all parameters are tuned using grey wolf optimization (GWO) algorithm for controlling the terminal voltage of AVR system. The response of the system using this controller is compared with other controllers using different new optimization methods in terms of transient analysis; also to test its performance; robustness analysis is performed on it in two types (model uncertainties and external disturbances). Simulation results reflect an efficient performance of PIDD2 controller also proved it is robust in facing disturbances and returning the system to its desired response.

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Continuous-Time and Event-Triggered Online Optimization for Linear Multi-Agent systems

arXiv

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arXiv 2022年

作者： Yu, Yang Li, Xiuxian Li, Li Xie, Lihua The Department of Control Science and Engineering Shanghai Research Institute for Autonomous Intelligent Systems Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China The School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

This paper studies the decentralized online convex optimization problem for heterogeneous linear multi-agent systems. Agents have access to their time-varying local cost functions related to their own outputs, and there are also time-varying coupling inequality constraints among them. The goal of each agent is to minimize the global cost function by selecting appropriate local actions only through communication between neighbors. We design a distributed controller based on the saddle-point method which achieves constant regret bound and sublinear fit bound. In addition, to reduce the communication overhead, we propose an event-triggered communication scheme and show that the constant regret bound and sublinear fit bound are still achieved in the case of discrete communications with no Zeno behavior. A numerical example is provided to verify the proposed algorithms. Copyright © 2022, The Authors. All rights reserved.

关键词： Cost functions

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Study of the Influence of Rolling Modes on the Operation of Interconnected Electric Drives of a Rolling Mill

Study of the Influence of Rolling Modes on the Operation of ...

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Advanced technology (KhPIWeek), IEEE KhPI Week on

作者： Valerii Tytiuk Alexey Kalinin Valeriy Druzhinin Victor Busher Oleksii Chornyi Dmytro Halushko Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Informative computer systems Abylkas Saginov Karaganda Technical University NPJSC Karaganda The Republic of Kazakhstan Department of Power Engineering Karaganda Industrial University NPJSC Temirtau The Republic of Kazakhstan Dept. of Electrical Engineering and Electronics National University “Odessa Maritime Academy” Odessa Ukraine Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Dept. of Electrical Engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

The paper is devoted to study of the influence of rolling modes on the performance of powerful interconnected electric drives of a hot rolling mill under the action of an electromagnetic coupling circuit between the electric drives of the roughing and finishing groups. The action of the electromagnetic coupling circuit manifests itself in the form of the influence of impact loads of synchronous electric drives on the angular velocity of direct current electric drives of the finishing group of the mill. The parameters of the electromagnetic coupling circuit are determined by the power supply scheme and equipment parameters. Values of impact loads applied to a synchronous motor depend on the rolling process parameters, in particular, the chemical composition of the rolled steel and the temperature of the ingot. The paper presents the results of calculating the rolling power for various rolling mode parameters. Using mathematical modeling in Simulink, numerical estimates of the influence of rolling modes on the magnitude of the voltage drop in the power supply unit and the drop in the angular velocity of the electric drive of the finishing group were obtained on the example of a wide-strip hot rolling mill 1700 of ArcelorMittal Temirtau JSC.

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Technical and Economic Assessment of Use Local Autonomous Sources of Energy Supply 25

Technical and Economic Assessment of Use Local Autonomous So...

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25th IEEE International Conference on Problems of Automated Electric Drive. Theory and Practice, PAEP 2020

作者： Zachepa, Iurii Chornyi, Oleksii Perekrest, Andrii Zachepa, Nataliia Zbyrannyk, Oksana Mykhalchenko, Ganna Kremenchuk Mykhailo Ostrohradskyi National University Systems of Automatic Control and Electric Drive Department Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Department of Economics and Management Kremenchuk Ukraine Ukrainian Engineering Pedagogics Academy Department of Economy of Enterprises and Management Kharkov Ukraine

ISBN: (纸本)9781728199351

The paper proves the economic feasibility of using a local autonomous source of energy supply, which is formed from electrical equipment of other functional purposes based on an asynchronous machine with capacitive self-excitation. To assess the technical and economic indicators of the effectiveness of introducing a local autonomous source of energy supply, the discounted method is adopted, where an indicator of savings from possible losses due to the exclusion of labor resources from production is used as an additional influence factor. © 2020 IEEE.

关键词： Energy resources

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Distributed control of Descriptor Networks: A Convex Procedure for Augmented Sparsity

arXiv

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arXiv 2021年

作者： Sperilă, Andrei Oară, Cristian Ciubotaru, Bogdan D. Sabău, Şerban Faculty of Automatic Control and Computers "Politehnica" University of Bucharest Sector 6 060042 Romania Electrical and Computer Engineering Department Stevens Institute of Technology HobokenNJ07030 United States

For networks of systems, with possibly improper transfer function matrices, we present a design framework which enables H∞ control, while imposing sparsity constraints on the controller’s coprime factors. We propose a convex and iterative optimization procedure with guaranteed convergence to obtain distributed controllers. By exploiting the robustness-oriented nature of our proposed approach, we provide the means to obtain sparse representations of our control laws that may not be directly supported by the network’s nominal model. © 2021, CC BY.

关键词： Convex optimization

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Towards Safe Neural Network Supported Model Predictive control

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IFAC-PapersOnLine 2020年第2期53卷 5246-5251页

作者： T. Zieger A. Savchenko T. Oehlschlägel R. Findeisen Laboratory for Systems Theory and Automatic Control Otto-von-Guericke University Magdeburg Germany Department of Powertrain Mechatronics iav GmbH Gifhorn Germany

Model Predictive control has proven to be a universal and flexible method to control complex nonlinear system with guaranteed constraint satisfaction. However, high dependency on model quality often renders it inappropriate for hard to model systems. On the other hand, machine learning methods show great performance when approximating functions based on data. This capability for learning with poor a priori knowledge, however, comes at the cost of low predictability and lack of safety guarantees. To overcome these drawbacks we illustrate how a neural network can be setup as a nonlinear feedforward control that augments the MPC control signal to approximate a desired control behaviour. For instance, it could aim to mimic the control behaviour of a human driver, while the underlying MPC exploits prior knowledge. Moreover, to preserve constraint satisfaction, we suggest to restrict the range of neural network outputs such that it intrinsically satisfies control input constraints. Subsequently, we represent the neural network control signal as a disturbance which enables the application of tube MPC to retain state constraints satisfaction at the cost of introducing some conservatism. We demonstrate these concepts via simulation, test and highlight both the advantages and the drawbacks of the proposed control structure.

关键词： Model predictive control Machine learning Neural networks Constraint satisfaction Tube model predictive control

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On the asymptotic optimality of cross-validation based hyper-parameter estimators for regularized least squares regression problems

arXiv

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arXiv 2021年

作者： Mu, Biqiang Chen, Tianshi Ljung, Lennart Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Data Science Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen518172 Hong Kong Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden

The asymptotic optimality (a.o.) of various hyper-parameter estimators with different optimality criteria has been studied in the literature for regularized least squares regression problems. The estimators include e.g., the maximum (marginal) likelihood method, Cp statistics, and generalized cross validation method, and the optimality criteria are based on e.g., the inefficiency, the expectation inefficiency and the risk. In this paper, we consider the regularized least squares regression problems with fixed number of regression parameters, choose the optimality criterion based on the risk, and study the a.o. of several cross validation (CV) based hyper-parameter estimators including the leave k-out CV method, generalized CV method, r-fold CV method and hold out CV method. We find the former three methods can be a.o. under mild assumptions, but not the last one, and we use Monte Carlo simulations to illustrate the efficacy of our findings. Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Exponential Consensus of Multiple Agents over Dynamic Network Topology: controllability, Connectivity, and Compactness

arXiv

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arXiv 2023年

作者： Ma, Qichao Qin, Jiahu Anderson, Brian D.O. Wang, Long Department of Automation University of Science and Technology of China Hefei230027 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China School of Engineering Australian National University ActonACT2601 Australia Center for Systems and Control College of Engineering Peking University Beijing100871 China

This paper investigates the problem of securing exponentially fast consensus (exponential consensus for short) for identical agents with finite-dimensional linear system dynamics over dynamic network topology. Our aim is to find the weakest possible conditions that guarantee exponentially fast consensus using a Lyapunov function consisting of a sum of terms of the same functional form. We first investigate necessary conditions, starting by examining the system (both agent and network) parameters. It is found that controllability of the linear agents is necessary for reaching consensus. Then, to work out necessary conditions incorporating the network topology, we construct a set of Laplacian matrix-valued functions. The precompactness of this set of functions is shown to be a significant generalization of existing assumptions on network topology, including the common assumption that the edge weights are bounded piecewise constant functions or continuous functions. With the aid of such a precompactness assumption and restricting the Lyapunov function to one consisting of a sum of terms of the same functional form, we prove that a joint (δ, T)-connectivity condition on the network topology is necessary for exponential consensus. Finally, we investigate how the above two "necessities" work together to guarantee exponential consensus. To partially address this problem, we define a synchronization index to characterize the interplay between agent parameters and network topology. Based on this notion, it is shown that by designing a proper feedback matrix and under the precompactness assumption, exponential consensus can be reached globally and uniformly if the joint (δ, T)-connectivity and controllability conditions are satisfied, and the synchronization index is not less than one. © 2023, CC BY-NC-ND.

关键词： Network topology

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