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Observer-based stabilization for discrete nonlinear semi-Markov jump singularly perturbed models with mode-switching delay

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Science China(Information Sciences) 2025年第4期68卷 389-390页

作者： Wenhai QI Runkun LI Ju H.PARK Zheng-Guang WU Huaicheng YAN School of Engineering Qufu Normal University Department of Electrical Engineering Yeungnam University Institute of Cyber-Systems and Control Zhejiang University Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology

Semi-Markov jump systems(S-MJMs) not only characterize hybrid systems but also address the limitations of Markov jump systems(MJMs) [1–3]. Due to their ability to exhibit multi-time-scale features, singularly perturbed models(SPMs) effectively model practical systems influenced by multiple time-scale phenomena [4]. In this study, the observer-based output feedback controller is asynchronous with the original system due to the time delay in the controller mode switching. A nonlinear plant with singularly perturbed parameters(SPPs) is represented using an interval type-2(IT2) fuzzy model [5].

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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Influence of inspiratory resistors on tracheal pressure during ventilation with decelerating flow

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Intensive Care Medicine – Paediatric and Neonatal 2025年第1期3卷 1-10页

作者： Werder, David Stankovic, Nikola Zander, Mark Oliver Serfözö, Peter Erb, Thomas Otto Hammer, Jürg Schmid Daners, Marianne Institute for Dynamic Systems and Control Department of Mechanical and Process Engineering ETH Zurich Zurich Switzerland Department of Anesthesiology University Children’S Hospital Basel University of Basel Basel Switzerland Product Development Group Zurich Department of Mechanical and Process Engineering ETH Zurich Zurich Switzerland Emergency Department Lausanne University Hospital Lausanne Switzerland Department of Pulmonology and Critical Care University Children’S Hospital Basel University of Basel Basel Switzerland

Understanding driving pressure is of general interest in lung mechanics, especially in ventilated neonatal and pediatric patients. The aim of this study was to investigate the effects of endotracheal tube size (ETT) and bi-directional linear flow resistors mimicking different degrees of tube and airway obstruction on tracheal pressure (Ptr) during ventilation with decelerating flow. A mechanical lung simulator with unchanged respiratory mechanics like the mimicked compliance and resistance, three ETTs (inner diameters of 7.5 mm, 5.5 mm, and 3.5 mm), and four different linear flow resistors were alternatively connected to a commercial ventilator operating in pressure-controlled mode. Four resistors mimicking various degrees of ETT obstructions were placed consecutively between the Y-piece and the ETT. Varying sequentially ETT size, resistance, and ventilator settings resulted in 90 sets of measurements. Data acquisition, signal processing, and data analysis were performed using Python. The results clarify that decreasing ETT sizes and increasing flow resistances cause an increase in the time necessary to reach zero-flow conditions both during in- and expiration. This results in a decrease of Ptr at the end of inspiration and an increase of Ptr at the end of expiration, if inspiratory and expiratory times remain unchanged. The degree to which peak inspiratory pressure overestimates Ptr (or plateau pressure) in decelerating flow can be substantial and increases with increasing flow resistance. This highlights the importance of measuring plateau pressure or Ptr to understand pressure dynamics delivered to the lung.

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Employing Different Hydrodynamic Models (Mike & Hec-Rac) to Predict the Extreme Flood in the Hron River, Slovakia and Provide the Adequate Mitigation Measures

SSRN

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SSRN 2025年

作者： Zeleňáková, Martina Kaya, Yunus Ziya Abd-Elhamid, Hany F. Garaj, Miroslav Fijko, Rastislav Gergeľová, Marcela Bindzárová Department of Environmental Engineering Faculty of Civil Engineering Technical University of Kosice Košice04001 Slovakia Department of Civil Engineering Faculty of Engineering Osmaniye Korkut Ata University Osmaniye80100 Turkey Department of Water and Water Structures Engineering Faculty of Engineering Zagazig University Zagazig44519 Egypt Department of Geodesy Cartography and Geographical Information Systems Faculty of Faculty of Mining Ecology Process Control and Geotechnologies Technical University of Kosice Košice04001 Slovakia

In this study, the abilities of two of the most popular flood modeling software, namely, HEC-RAS and MIKE+, were used for flood modeling in the Hron River in East Slovakia. For modeling purposes, various discharge values of the River from one year to hundred years peak discharge were considered. The vulnerability of the catchment for each period was modeled and visualized using both software. The HEC-RAS and MIKE+ outputs showed that the study area is vulnerable to flood for high-frequency peak discharge values. The outputs of both 2D hydrodynamic approaches were found to be close to each other in various flow conditions. The comparisons of the MIKE+ and HEC-RAS showed that Hron River dimensions for the given catchment are only sufficient to transfer a one-year peak discharge value safely. The outputs of the models exhibited that the study area is not safe in case of ten-year peak discharge value and the risk of the floods getting the highest level in case of hundred-year peak discharge. Due to the models’ findings, it is seen that the area is vulnerable to flood, and three different mitigation scenarios were proposed and analyzed including change in river bed dimensions and rise of the levee on the right and left river bank to protect the area from flood risks. © 2025, The Authors. All rights reserved.

关键词： Floods

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Stealthy Attacks on Sampled-Data control and Encryption-Based Countermeasures

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IEEE Transactions on Automatic control 2025年

作者： Shang, Jun Li, Yuzhe Chen, Tongwen Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

This paper investigates stealthy attacks on sampled-data control systems, where a continuous process is sampled periodically, and the resultant discrete output and control signals are transmitted through dual channels in wireless communication networks. Acknowledging the vulnerability of these transmitted data to cyber threats, we analyze two types of stealthy attacks that compromise either one or both channels. We explicitly present the necessary and sufficient conditions for the existence of stealthy single-channel attacks. To mitigate these security risks, we implement encryption-based countermeasures, including linear time-invariant and periodic encryption methods. We detail sufficient conditions under which these encryption strategies effectively thwart single- and dual-channel stealthy attacks. The effectiveness of these approaches and the theoretical findings are demonstrated through numerical simulations. © 1963-2012 IEEE.

关键词： Cyber attacks

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Federated K-means clustering via dual decomposition-based distributed optimization

Franklin Open

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Franklin Open 2025年 10卷

作者： Yfantis, Vassilios Wagner, Achim Ruskowski, Martin Chair of Machine Tools and Control Systems Department of Mechanical and Process Engineering RPTU Kaiserslautern-Landau Gottlieb-Daimler-Straße 42 Kaiserslautern 67663 Germany Innovative Factory Systems German Research Center for Artificial Intelligence Trippstadter Str. 122 Kaiserslautern 67663 Germany

The use of distributed optimization in machine learning can be motivated either by the resulting preservation of privacy or the increase in computational efficiency. On the one hand, training data might be stored across multiple devices. Training a global model within a network where each node only has access to its confidential data requires the use of distributed algorithms. Even if the data is not confidential, sharing it might be prohibitive due to bandwidth limitations. On the other hand, the ever-increasing amount of available data leads to large-scale machine learning problems. By splitting the training process across multiple nodes its efficiency can be significantly increased. This paper aims to demonstrate how dual decomposition can be applied for distributed training of K-means clustering problems. After an overview of distributed and federated machine learning, the mixed-integer quadratically constrained programming-based formulation of the K-means clustering training problem is presented. The training can be performed in a distributed manner by splitting the data across different nodes and linking these nodes through consensus constraints. Finally, the performance of the subgradient method, the bundle trust method, and the quasi-Newton dual ascent algorithm are evaluated on a set of benchmark problems. The main benefit stemming from the formulation of the clustering problem as a mixed-integer program and from the use of dual decomposition within a federated learning framework, apart from the preservation of privacy, is the computation of a lower bound of the objective of the overall clustering problem. In this way, the worst-case distance of any found solution to the global optimum can be easily assessed. While the mixed-integer programming-based formulation of the clustering problems suffers from weak integer relaxations, the presented approach can potentially be used to enable an efficient solution in the future, both in a central and distributed sett

关键词： Clustering Distributed optimization Dual decomposition Federated learning

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Excellent Defluorination Performance in Nico-Layered Metal Oxide Based Asymmetric Flow Capacitive Deionization System

SSRN

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SSRN 2025年

作者： Hu, Dongyang Liu, Yongqi Dai, Zhongde Sabale, Sandip Kim, Deok-Kee Li, Yiming Xiong, Jian Zheng, Yu Li, Yuping Zhou, Qiongzhi Shen, Jian College of Environment and Resources Xiangtan University Xiangtan411105 China Hunan Brunp Recycling Technology Co. Ltd. Changsha410604 China School of Carbon Neutrality Future Technology Sichuan University Chengdu610065 China Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of School of Ecology and Environment Tibet University Lhasa850000 China Beijing Engineering Research Center of Process Pollution Control Division of Environment Technology and Engineering Key Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

The high concentration of fluoride (F-) ions in contaminated water has become an urgent challenge for public health and environmental safety. In this contribution, we adopted asymmetric flow electrode capacitive deionization (FCDI) technique to remove F- ions, selecting NiCo layered metal oxide/carbon black (NiCo-LMO/CB) and Prussian blue analogs (cobalt hexacyanocobaltate, CoHCC) as the flow anode and cathode materials, respectively. As expected, the NiCo-LMO/CB flow electrode demonstrated excellent performance in terms of F- removal efficiency (68.54%), F- adsorption capacity (13.78 mg/g), and energy consumption (5.39 J/mg) when treating 1000 mg/L NaF solution under 1.2 V cell voltage. Combining electrochemical characterizations with structural analysis, such excellent defluorination performance of NiCo-LMO/CB can be ascribed to both electrostatic attraction and flexible ions intercalation. Hopefully, this work provides new ideas for defluorination of high concentration fluoridated wastewater via adopting asymmetric FCDI. © 2025, The Authors. All rights reserved.

关键词： Deionized water

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Quantized Distributed Nonconvex Optimization Algorithms with Linear Convergence under the Polyak–Lojasiewicz Condition

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IEEE Transactions on Automatic control 2025年

作者： Xu, Lei Yi, Xinlei Sun, Jiayue Shi, Yang Johansson, Karl H. Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 2Y2 Canada Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai201804 China KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden

This paper considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To reduce the required communication capacity, we introduce an encoder–decoder scheme. By integrating it with distributed gradient tracking and proportional integral algorithms, respectively, we then propose two quantized distributed nonconvex optimization algorithms. Assuming the global cost function satisfies the Polyak–Lojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that our proposed algorithms linearly converge to a global optimal point. Moreover, we show that a low data rate is sufficient to guarantee linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical examples. © 1963-2012 IEEE.

关键词： Cost functions

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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