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Observer-based resilient cooperative output regulation for nonlinear multiagent systems with time-varying parameters and DoS attacks

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2025年第6期56卷 1332-1346页

作者： Guo, Ming-Juan Li, Yuan-Xin Liaoning Univ Technol Coll Sci Jinzhou 121001 Liaoning Peoples R China

This paper aims to address the cooperative output regulation (COR) problem of nonlinear multiagent systems (MASs) with time-varying parameters under denial-of-service (DoS) attacks. First, to address the challenges of unavailable leader signals and non-differentiability issue caused by the DoS attacks, a class of first-order low-pass filters is employed to develop a novel distributed resilient observer, which accurately estimate the exosystem state with the existence of high-order derivatives. Then, by viewing the output of observer as the reference signal, a distributed resilient controller is designed for each follower to address the reference-tracking problem. By introducing a smooth function with positive integrable time-varying function, novel adaptive laws are developed and incorporated with the controller design to effectively compensate for the unknown time-varying parameters. By utilising Lyapunov stability theory, the asymptotic convergence of output regulation error can be ensured. Finally, simulation results are conducted to verify the validity of the designed method.

关键词： Cooperative output regulation control nonlinear multi-agent systems time-varying parameters DoS attacks backstepping method

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Bayesian autoregressive online change-point detection with time-varying parameters

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2025年 142卷

作者： Tsaknaki, Ioanna-Yvonni Lillo, Fabrizio Mazzarisi, Piero Univ Siena Siena Italy Scuola Normale Super Pisa Pisa Italy Univ Bologna Dipartimento Matemat Bologna Italy

Change points in real-world systems mark significant regime shifts in system dynamics, possibly triggered by exogenous or endogenous factors. These points define regimes for the time evolution of the system and are crucial for understanding transitions in financial, economic, social, environmental, and technological contexts. Building upon the Bayesian approach introduced in Adams and MacKay (2007), we devise a new method for online change point detection in the mean of a univariate time series, which is well suited for real-time applications and is able to handle the general temporal patterns displayed by data in many empirical contexts. We first describe time series as an autoregressive process of an arbitrary order. Second, the variance and correlation of the data are allowed to vary within each regime driven by a scoring rule that updates the value of the parameters for a better fit of the observations. Finally, a change point is detected in a probabilistic framework via the posterior distribution of the current regime length. By modeling temporal dependencies and time-varying parameters, the proposed approach enhances both the estimate accuracy and the forecasting power. Empirical validations using various datasets demonstrate the method's effectiveness in capturing memory and dynamic patterns, offering deeper insights into the non-stationary dynamics of real-world systems.

关键词： time series analysis Change point detection Long memory time-varying parameters Bayesian inference

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Identification of time-varying parameters of a monthly Budyko function in US MOPEX catchments and its implications

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Journal of Hydrology: Regional Studies 2025年 59卷

作者： Liu, Weibo Liu, Pan Cheng, Lei Zhang, Xiaojing Zhou, Liting State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan 430072 China Hubei Provincial Key Lab of Water System Science for Sponge City Construction Wuhan University Wuhan 430072 China Research Institute for Water Security (RIWS) Wuhan University Wuhan 430072 China China Yangtze Power Co. Ltd Yichang 443133 China Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science Yichang 443133 China

Study region: Model Parameter Estimation Experiment (MOPEX) catchments across the continental United States. Study focus: The Budyko framework provides a simple yet useful method for estimating evapotranspiration (ET), traditionally used at the mean annual scale due to the assumption of constant catchment water storage. Under changing conditions, time-invariant model parameters may not fully capture variations in the underlying surface. Several studies have extended the Budyko framework to the monthly scale;however, few studies have identified monthly time-varying Budyko model parameters and explored the factors driving their variability. This study develops a method for identifying time-varying parameters κ and y₀ of a two-parameter Budyko model using the Ensemble Kalman Filter. Additionally, Extreme Gradient Boosting is used to explore the factors influencing time-varying parameters. New hydrological insights for the study region: Monthly time-varying parameters are effectively identified through simultaneous assimilation of ET and runoff observations, achieving a Kling-Gupta Efficiency of 0.94 in ET simulation. (2) 11 and 2 catchments display change points and trends in parameter κ, respectively, while 64 and 48 catchments exhibit change points and trends in y₀, respectively. (3) Parameter κ is mainly influenced by climatic factors in low-latitude, storage-related factors in high-latitude, and normalized difference vegetation index in central U.S. catchments, respectively. y₀ is mainly influenced by total soil moisture, along with vegetation and agricultural land cover changes in the central region. © 2025 The Authors

关键词： Ensemble Kalman filter Evapotranspiration estimation Monthly Budyko function MOPEX catchments time-varying parameters

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time-varying parameters of the hydrological simulation model under a changing environment

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JOURNAL OF HYDROLOGY 2024年 643卷

作者： Liu, Ruimin Luo, Ying Wang, Qingrui Wang, Yue Liu, Yue Xia, Xinghui Jiang, Enhui Beijing Normal Univ Sch Environm State Key Lab Water Environm Simulat 19 Xinjiekouwai St Beijing 100875 Peoples R China Yellow River Water Conservancy Commiss Yellow River Water Conservancy Res Inst Zhengzhou 450003 Peoples R China Minist Water Resources Key Lab Lower Yellow River Channel & Estuary Regul Zhengzhou 450003 Peoples R China

time-varying parameters of hydrological models play a crucial role in capturing the dynamic nature of hydrological processes and nonpoint source pollution under changing environments. In this study, the SWAT-DynamicParam model was developed by integrating the Soil and Water Assessment Tool (SWAT) model with an ensemble Kalman filter (EnKF) to identify and analyze time-varying parameters. The results showed that the SWAT-DynamicParam framework is capable of effectively identifying multiple time-varying characteristics of parameters. The combination of flow and evapotranspiration (ET) data can accurately identify changes in CANMX (Maximum canopy storage), CN2 (Initial SCS runoff curve number for moisture condition II) and ALPHA_BF (Baseflow alpha factor), with the Relative Absolute Error 5%. Compared with using static parameters, the model simulation effect was improved by more than 30% when using time-varying parameters. In addition, the variation in parameters showed significant spatio-temporal heterogeneity. The change trend of parameters at Weijiabao station showed the largest fluctuation, with a range greater than 100. Temporally, CN2 and ALPHA_BF both reached peak values in 2008 while the trend of CANMX was the opposite. At the monthly scale, the trends of ALPHA_BF and CANMX were similar: Values were at a minimum in April and May, with the range is 2.57 times the minimum value. The CN2 ' s lowest value was recorded in August, whereas December saw its highest, reaching 82. In summary, the SWAT-DynamicParam model enhanced simulation accuracy by over 30%, demonstrating the pivotal role of accurately identified time-varying parameters in capturing the dynamic nature of hydrological processes and their response to environmental changes.

关键词： time-varying parameters SWAT-DynamicParam framework Soil and Water Assessment Tool model Ensemble Kalman filter Multisource observation data

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time-varying parameters from the same period in previous years to improve runoff forecasting

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JOURNAL OF HYDROLOGY 2024年 631卷

作者： Zhang, Xiaojing Liu, Pan Cheng, Lei Zhou, Liting Liu, Weibo Luo, Xinran Wuhan Univ State Key Lab Water Resources Engn & Management Wuhan 430072 Peoples R China Wuhan Univ Res Inst Water Secur RIWS Wuhan 430072 Peoples R China Wuhan Univ Hubei Prov Key Lab Water Syst Sci Sponge City Cons Wuhan 430072 Peoples R China China Yangtze Power Co Ltd Yichang 443133 Peoples R China Hubei Key Lab Intelligent Yangtze & Hydroelect Sci Yichang 443133 Peoples R China Wuhan Univ State Key Lab Water Resources & Hydropower Engn Sc Wuhan 430072 Peoples R China

The time-varying parameter functional (TVPF) method has shown promise in improving runoff forecasting under climate change and human activities. However, it has three notable limitations: data availability, increased model complexity, and the inability to update with newly measured data. To address these challenges, this study proposes an improved runoff forecasting method that relies solely on time-varying parameters from the same period in previous years. The proposed method comprises four steps: (1) identification of time-varying parameters from historical observations;(2) estimation of the current-year parameters by averaging the time-varying parameters from the same period in previous years;(3) runoff forecasts using the estimated current-year parameters;(4) continuous identification and estimation of parameters with newly measured data for each year, enabling a rolling forecast of runoff. The proposed method is compared with both the constant parameter method and TVPF method, using the Xun River and Zuo River basins as case studies. The results reveal that (1) parameters from the same period in the previous three years yield the best runoff forecasts in the Xun River basin, while parameters from the same period in the previous five years produce the best runoff forecasts in the Zuo River basin;(2) the proposed method significantly improves the water balance index (WBI) compared to the TVPF method, providing either superior or comparable performance in structural risk minimization (SRM) evaluation. Overall, this study provides an approach to forecast runoff in a changing environment that reduces data requirements, simplifies model complexity, and improves WBI performance.

关键词： Hydrologic modeling time-varying parameters Runoff forecasting

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time-varying parameters in monetary policy rules: a GMM approach

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JOURNAL OF ECONOMIC STUDIES 2024年第9期51卷 148-176页

作者： Anderl, Christina Caporale, Guglielmo Maria London South Bank Univ London England Brunel Univ London England

PurposeThe article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over ***/methodology/approachThis paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) *** monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under ***/valueIt provides new evidence on changes over time in monetary policy rules.

关键词： Taylor rules Monetary policy rules Generalised methods of moments time-varying parameters C14 C52 E52 E58

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time-varying parameters: a critical introduction

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Structural Change and Economic Dynamics 1995年第2期6.0卷 237-260页

作者： Tucci, Marco P. Facolta di Giurisprudenza 53100 Siena Piazza San Francesco 7 Italy

One of the assumptions behind standard econometric techniques is that coefficients are fixed throughout the whole sample period or over all the cross-sectional units. This implies that the economic structure generating the data does not change, but the parameters characterizing the micro-units, along with their aggregate counterparts, do change. The present paper contains an introduction to the method of modelling parameters varying over time. In contrast to most of the existing, highly technical, surveys in this area, this paper stresses the intuitive aspects of the assumptions, limits and potentialities characterizing the time-varying parameters approach. Moreover, the most appropriate economic applications for each model are indicated, so the non-econometrician has a way of knowing what kind of problem can be fruitfully solved by this technique and what to expect from it. © 1995 Elsevier Science B.V.

关键词： C1 C2 Modelling Structural change time-varying parameters

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time-varying parameters Based Gyrocompass Alignment for Marine SINS with Large Heading Misalignment

Time-varying Parameters Based Gyrocompass Alignment for Mari...

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IEEE/ION Position, Location and Navigation Symposium (PLANS)

作者： Sun, Feng Xia, Jianzhong Ben, Yueyang Lan, Haiyu Harbin Engn Univ Coll Automat Harbin Peoples R China Univ Calgary Dept Geomat Engn Calgary AB Canada

ISBN: (纸本)9781479933204

Gyrocompass alignment algorithm is a fine alignment technique based on gyrocompass effect and loop feedback control theory. Conventional strapdown gyrocompass alignment methods are based on the assumption that the system has a small heading misalignment angle. However, a large heading misalignment angle would exist during the alignment duration under some conditions, especially for marine strapdown inertial navigation system (SINS). This paper proposed a time-varying parameters based gyrocompass alignment method to solve this problem. Error model of gyrocompass alignment with large heading misalignment error is presented and an appropriate multi-parameter setting is given, a proper scenario for parametric switch is also derived. Simulation and experimental results show that the proposed method has better alignment performance than conventional ones when the system has a large heading misalignment angle.

关键词： SINS gyrocompass alignment time-varying parameters large heading misalgnment

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Adaptive Containment Control for Fractional-Order Nonlinear Multi-Agent Systems With time-varying parameters

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1627-1638页

作者： Yang Liu Huaguang Zhang Yingchun Wang Hongjing Liang the College of Information Science and Engineering Northeastern UniversityShenyang 110004China the State Key Laboratory of Synthetical Automation for Process Industries and also with the School of Information Science and EngineeringNortheastern UniversityShenyang 110004China the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and *** using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is *** command filter is introduced to solve the complexity problem inherent in adaptive backstepping ***,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is ***,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the *** on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic ***,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.

关键词： Adaptive backstepping control command filter fractional-order multi-agent system time-varying parameters

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A Variational Approach for Designing Infinite Impulse Response Filters With time-varying parameters

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2018年第4期65卷 1303-1313页

作者： Toledo de la Garza, Karel Torres Gomez, Jorge de lamare, Rodrigo C. Fernandez-Getino Garcia, Maria Julia Univ Santiago Chile Dept Elect Engn Santiago 9170124 Chile CUJAE Univ Dept Telecommun & Telemat Havana 11901 Cuba Pontificial Catolic Univ Rio De Janeiro Ctr Telecommun Res BR-22451900 Rio De Janeiro Brazil Carlos III Univ Madrid Dept Signal Theory & Commun Madrid 28911 Spain

Filter design with short transient state is a problem encountered in many fields of circuits, systems, and signal processing. In this paper, a novel low-pass filter design technique with time-varying parameters is introduced in order to minimize the rise-time parameter. Through the use of calculus of variations a method is developed to obtain the optimal closed-form expression for adjusting the parameters. In this context, two cases are addressed: the ideal case in which infinite bandwidth is required and a solution of finite bandwidth. The latter is obtained by means of a proper constraint formulation in the frequency domain. The proposed filter achieves the shortest rise time and allows better preservation of the edge shape in comparison with other existing filtering methods. The analysis, synthesis, and performance of the proposed system are discussed and illustrated with the aid of simulations.

关键词： Filter design rise-time time-varying parameters calculus of variations

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