Relevant bibliographies by topics / Uncertain time-Varying parameter

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Uncertain time-Varying parameter'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Uncertain time-Varying parameter"

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Yang, Fan, Wen Wang, Lixiang Li, Mingwen Zheng, Yanping Zhang, and Zhenying Liang. "Finite-time parameter identification of fractional-order time-varying delay neural networks based on synchronization." Chaos: An Interdisciplinary Journal of Nonlinear Science 33, no. 3 (2023): 033146. http://dx.doi.org/10.1063/5.0137598.

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We research the finite-time parameter identification of fractional-order time-varying delay neural networks (FTVDNNs) based on synchronization. First, based on the fractional-order Lyapunov stability theorem and feedback control idea, we construct a synchronous controller and some parameter update rules, which accomplish the synchronization of the drive-response FTVDNNs and complete the identification of uncertain parameters. Second, the theoretical analysis of the synchronization method is carried out, and the stable time is calculated. Finally, we give two examples for simulation verificatio
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Chen, Y. H. "Decentralized Adaptive Robust Control Design: The Uncertainty is Time Varying." Journal of Dynamic Systems, Measurement, and Control 113, no. 3 (1991): 515–18. http://dx.doi.org/10.1115/1.2896441.

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We consider a class of nonlinear uncertain interconnected systems with time-varying uncertainty. The uncertainty may arise within each system as well as in the interconnections. The uncertainty is assumed bounded but the bound is unknown. No a priori statistical information is imposed. Decentralized adaptive robust control is proposed for each system. The control has two parts. First, an adaptive scheme for the estimation of the bound is constructed. Second, a robust control, which is based on the adaptive parameter, is adopted for each system.
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Zhang, Jiashuo, Tingqing Ye, Xiaoya Xu, Yang Liu, and Haoran Zheng. "Parameter Estimation in Multifactor Uncertain Differential Equation with Symmetry Analysis for Stock Prediction." Symmetry 17, no. 4 (2025): 620. https://doi.org/10.3390/sym17040620.

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Multifactor uncertain differential equations (MUDEs) are effective tools to model dynamic systems under multi-source noise. With the widespread use of MUDEs, parameter estimation as the bridge between the observed data and the MUDE becomes increasingly important. Thus, how to estimate unknown parameters in a MUDE under a multi-source noise environment is a challenge. To address this, this paper innovatively proposes a moment method to estimate the unknown parameters in a MUDE and illustrates two numerical examples to show the process of estimating parameters. Furthermore, since the system or e
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HUANG, HE, HAN-XIONG LI, and JUE ZHONG. "MASTER-SLAVE SYNCHRONIZATION OF GENERAL LUR'E SYSTEMS WITH TIME-VARYING DELAY AND PARAMETER UNCERTAINTY." International Journal of Bifurcation and Chaos 16, no. 02 (2006): 281–94. http://dx.doi.org/10.1142/s0218127406014800.

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This paper deals with the problem of master-slave synchronization for uncertain Lur'e systems via time-varying delay feedback control. The parametric uncertainty is assumed to be norm bounded. Several new and sufficient conditions are presented such that the uncertain Lur'e master and slave systems are synchronous for all admissible uncertainties. These synchronization criteria are dependent on the size of time delay, which can be expressed by means of matrix inequalities. The adopted method is based on defining a new Lyapunov–Krasovskii function and using some inequalities techniques. Our res
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Mukdasai, Kanit. "Robust Exponential Stability for LPD Discrete-Time System with Interval Time-Varying Delay." Journal of Applied Mathematics 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/237430.

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This paper investigates the problem of robust exponential stability for uncertain linear-parameter dependent (LPD) discrete-time system with delay. The delay is of an interval type, which means that both lower and upper bounds for the time-varying delay are available. The uncertainty under consideration is norm-bounded uncertainty. Based on combination of the linear matrix inequality (LMI) technique and the use of suitable Lyapunov-Krasovskii functional, new sufficient conditions for the robust exponential stability are obtained in terms of LMI. Numerical examples are given to demonstrate the
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Shao, Xueying, Qing Lu, Hamid Reza Karimi, and Jin Zhu. "New Results on Passivity Analysis for Uncertain Neural Networks with Time-Varying Delay." Abstract and Applied Analysis 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/303575.

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The paper investigates the stability and passivity analysis problems for a class of uncertain neural networks with time-delay via delta operator approach. Both the parameter uncertainty and the generalized activation functions are considered in this paper. By constructing an appropriate Lyapunov-Krasovskii functional, some new stability and passivity conditions are obtained in terms of linear matrix inequalities (LMIs). The main characteristic of this paper is to obtain novel stability and passivity analysis criteria for uncertain neural networks with time-delay in the delta operator system fr
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Iqbal, Muhammad Naveed, Jian Xiao, and Weiming Xiang. "Parameter-dependent finite-time observer design for time-varying polytopic uncertain switched systems." Journal of the Franklin Institute 351, no. 3 (2014): 1657–72. http://dx.doi.org/10.1016/j.jfranklin.2013.12.007.

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Hu, Jingting, Guixia Sui, Shengli Du, and Xiaodi Li. "Finite-Time Stability of Uncertain Nonlinear Systems with Time-Varying Delay." Mathematical Problems in Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/2538904.

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The problem of finite-time stability for a class of uncertain nonlinear systems with time-varying delay and external disturbances is investigated. By using the Lyapunov stability theory, sufficient conditions for the existence of finite-time state feedback controller for this class of systems are derived. The results can be applied to finite-time stability problems of linear time-delay systems with parameter uncertainties and external disturbances. Finally, two numerical examples are given to demonstrate the effectiveness of the obtained theoretical results.
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Chen, Fu, Shugui Kang, and Fangyuan Li. "Stability and Stabilization for Polytopic LPV Systems with Parameter-Varying Time Delays." Mathematical Problems in Engineering 2019 (May 5, 2019): 1–12. http://dx.doi.org/10.1155/2019/4924963.

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In this paper, we deal with the problem of stability and stabilization for linear parameter-varying (LPV) systems with time-varying time delays. The uncertain parameters are assumed to reside in a polytope with bounded variation rates. Being main difference from the existing achievements, the representation of the time derivative of the time-varying parameter is under a polytopic structure. Based on the new representation, delay-dependent sufficient conditions of stability and stabilization are, respectively, formulated in terms of linear matrix inequalities (LMI). Simulation examples are then
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Liu, Yan, Hong Sheng Lin, Li Mei Liu, and Ying Li. "A Parameter-Dependent Approach to Robust H∞ Control of Norm Bounded Uncertain Systems." Applied Mechanics and Materials 701-702 (December 2014): 645–53. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.645.

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A new approach to analyze and synthesize linear uncertain systems with time varying norm bounded uncertainty is presented in this paper. First, the uncertainty set is separated into several different sets according to the maximum singular value of uncertainty.Based on the new classification, the original uncertain system is transformed into a Markovian jump system. Second, via a parameter-dependent Lyapunov function, the problems of robust H∞ analysis and synthesis is studied.Based on this, two sufficient conditions for designing parameter-dependent controllers are established. Finally, numeri
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Dissertations / Theses on the topic "Uncertain time-Varying parameter"

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Hego, Axelle. "Analyse de sensibilité sur un modèle hydrologique de toiture végétalisée." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0161.

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Ces dernières décennies, les surfaces imperméables des zones urbaines favorisent la saturation des systèmes d'évacuation. Dans le but de réduire l'impact de cette imperméabilité, l'installation de toitures végétalisées est une solution intéressante pour retenir et ralentir les eaux de pluie avant leur arrivée dans les réseaux. Une étude approfondie du comportement hydrique de ces structures est nécessaire pour la mise en place de toitures végétalisées performantes dans les éco-quartiers par exemple. Les performances hydriques sont caractérisées par la teneur en eau à l'intérieur des différente
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Doehr, Rachel M. "Adventures at the Zero Lower Bound: A Bayesian Time-Varying Parameter Vector Autoregressive Analysis of Monetary Policy Uncertainty Shocks." Scholarship @ Claremont, 2016. http://scholarship.claremont.edu/cmc_theses/1318.

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Using survey-based measures of future interest rate expectations from the Blue Chip Economic Indicators and the Survey of Professional Forecasters, we examine the relationship between monetary policy uncertainty, captured as the dispersion of interest rate forecasts, and fluctuations in real economic activity and core inflation. We use a flexible time-varying parameter vector autoregression (TVP-VAR) model to clearly isolate the dynamic effects of shocks to monetary policy uncertainty. To further study possible a possible nonlinear relationship between monetary policy uncertainty and the macro
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Juutilainen, I. (Ilmari). "Modelling of conditional variance and uncertainty using industrial process data." Doctoral thesis, University of Oulu, 2006. http://urn.fi/urn:isbn:9514282620.

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Abstract This thesis presents methods for modelling conditional variance and uncertainty of prediction at a query point on the basis of industrial process data. The introductory part of the thesis provides an extensive background of the examined methods and a summary of the results. The results are presented in detail in the original papers. The application presented in the thesis is modelling of the mean and variance of the mechanical properties of steel plates. Both the mean and variance of the mechanical properties depend on many process variables. A method for predicting the probability o
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Ganguly, Shreyan. "Modeling Nonstationarity Using Locally Stationary Basis Processes." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563408374215259.

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Tang, Yao-Tsuen, and 湯堯存. "Observer-Based Fuzzy Adaptive Controller Design forNonlinear Systems with Time-Varying Uncertain Parameters." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/57225600500655951907.

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碩士<br>大同大學<br>電機工程學系(所)<br>94<br>In this thesis, we propose an indirect adaptive fuzzy control scheme combined with state estimation for continuous-time multiple-input-multiple-output (MIMO) nonlinear systems with time-varying parametric uncertainties where the state information is not available. The proposed observer-based indirect adaptive fuzzy control employs a fuzzy system to approximate the time-varying parametric uncertainties, which are periodic and the only prior knowledge is the periodicity, to obtain fast parameter adaptation and fast convergence of the tracking error. Based on the
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Books on the topic "Uncertain time-Varying parameter"

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Chang-Jin, Kim. Sources of monetary growth uncertainty and economic activity: The time-varying-parameter model with heteroskedasticity in the disturbance terms. York University, Dept. of Economics, 1990.

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Amato, Francesco. Robust Control of Linear Systems Subject to Uncertain Time-Varying Parameters. Springer London, Limited, 2006.

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Robust Control of Linear Systems Subject to Uncertain Time-Varying Parameters. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-33276-6.

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Robust Control of Linear Systems Subject to Uncertain Time-Varying Parameters. Springer, 2006.

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Book chapters on the topic "Uncertain time-Varying parameter"

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Fu, Minyue, and Huaizhong Li. "Model Following Robust Control of Linear Time-Varying Uncertain Systems." In Robustness of Dynamic Systems with Parameter Uncertainties. Birkhäuser Basel, 1992. http://dx.doi.org/10.1007/978-3-0348-7268-3_26.

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Schaeffner, Maximilian, and Roland Platz. "Linear Parameter-Varying (LPV) Buckling Control of an Imperfect Beam-Column Subject to Time-Varying Axial Loads." In Model Validation and Uncertainty Quantification, Volume 3. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54858-6_11.

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Yoo, Seog-Hwan, and Byung-Jae Choi. "A Balanced Model Reduction for T-S Fuzzy Systems with Uncertain Time Varying Parameters." In Computational and Information Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30497-5_24.

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Kashkevich, Svitlana, Oleksiy Buyalo, Olha Matsyi, Anastasiia Voznytsia, Daniil Krant, and Kostiantin Radchenko. "Scientific and methodological apparatus for processing diverse data in automated control systems." In DECISION SUPPORT SYSTEMS: MATHEMATICAL SUPPORT. TECHNOLOGY CENTER PC, 2025. https://doi.org/10.15587/978-617-8360-13-9.ch4.

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This section of the study proposes the conceptual foundations for the use of artificial intelligence in intelligent decision support systems. In the course of the research, the authors:– justified the feasibility of using artificial intelligence theory for processing heterogeneous data in automated control systems;– developed a methodology for data distribution in automated control systems;– designed a model for evaluating the process of heterogeneous data processing in automated troop control systems using expert information;– improved the methodology for configuring an information system to
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Fu, Minyue, Lihua Xie, and Carlos E. de Souza. "H ∞ Control for Linear Systems with Time-Varying Parameter Uncertainty *." In CONTROL of UNCERTAIN DYNAMIC SYSTEMS. CRC Press, 2020. http://dx.doi.org/10.1201/9781003067702-6.

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Cerone, V., D. Piga, and D. Regruto. "Set-membership identification of input-output LPV models with uncertain time-varying parameters." In Linear Parameter-Varying System Identification. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814355452_0003.

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Thajeel Jawad, Al-Bittar Tamara, Ahmed Ashraf, and Soubra Abdul-Hamid. "Probabilistic Analysis at Ultimate Limit State of Strip Footings Resting on a Spatially Varying Soil Using Subset Simulation Approach." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-326.

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The failure probability of geotechnical structures with spatially varying soil properties is generally computed using Monte Carlo simulation (MCS) methodology. This approach is well known to be very time-consuming when dealing with small failure probabilities. One alternative to MCS is the subset simulation approach. This approach was mainly used in the literature in cases where the uncertain parameters are modelled by random variables. In this paper, it is employed in the case where the uncertain parameters are modelled by random fields because the spatial variability of the soil properties h
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Thajeel Jawad, Al-Bittar Tamara, Ahmed Ashraf, and Soubra Abdul-Hamid. "Probabilistic Analysis at Ultimate Limit State of Strip Footings Resting on a Spatially Varying Soil Using Subset Simulation Approach." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-328.

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The failure probability of geotechnical structures with spatially varying soil properties is generally computed using Monte Carlo simulation (MCS) methodology. This approach is well known to be very time-consuming when dealing with small failure probabilities. One alternative to MCS is the subset simulation approach. This approach was mainly used in the literature in cases where the uncertain parameters are modelled by random variables. In this paper, it is employed in the case where the uncertain parameters are modelled by random fields, because the spatial variability of the soil properties
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Rogers, Alexander W., Ziqi Song, Fernando Vega Ramon, Keju Jing, and Dongda Zhang. "Hybrid Modelling Under Uncertainty: Effects of Model Greyness, Data Quality and Data Quantity." In Machine Learning and Hybrid Modelling for Reaction Engineering. Royal Society of Chemistry, 2023. http://dx.doi.org/10.1039/bk9781837670178-00208.

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Previous chapters have demonstrated how, by combining data-driven and mechanistic methods, hybrid modelling provides a cost-effective solution to modelling complex (bio)chemical reaction kinetics when the underlying mechanisms are not fully understood. However, the question of how much kinetic information to incorporate into a hybrid model (i.e., the ‘greyness’ of a hybrid model) remains to be systematically addressed. Therefore, to illustrate the effect of model greyness on accuracy and reliability, in this chapter, we built three hybrid models for predicting the kinetics of a complex biochem
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Mansouri, Majdi, Benjamin Dumont, and Marie-France Destain. "Modeling and Prediction of Time-Varying Environmental Data Using Advanced Bayesian Methods." In Exploring Innovative and Successful Applications of Soft Computing. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4785-5.ch007.

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The problem of state/parameter estimation represents a key issue in crop models, which are nonlinear, non-Gaussian, and include a large number of parameters. The prediction errors are often important due to uncertainties in the equations, the input variables, and the parameters. The measurements needed to run the model and to perform calibration and validation are sometimes not numerous or known with some uncertainty. In these cases, estimating the state variables and/or parameters from easily obtained measurements can be extremely useful. In this chapter, the authors address the problem of mo
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Conference papers on the topic "Uncertain time-Varying parameter"

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Zhu, Mengjia, Oliver Pennington, Sam Kay, Amin Zarei, Michael Short, and Dongda Zhang. "Optimization-based operational space design for effective bioprocess performance under uncertainty." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.131628.

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Maintaining consistent product quality and yield in bioprocess operations is challenging due to uncertainties inherent in biological systems. Thus, robust strategies are essential to ensure key performance indicators (KPIs), such as product concentration and yield, are consistently met despite the uncertainties. Real-time feedback co Interntrol, though widely used, is often impractical due to its reliance on expensive sensors, rapid data processing, and high-speed control actions. This paper proposes a novel approach to address these challenges by identifying the operational space for control
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Gill, Hyunjune, and Seongkyu Lee. "Uncertainty Quantification of Unsteady Loading Noise of a Hovering Rotor Using Polynomial Chaos Expansion." In Vertical Flight Society 81st Annual Forum and Technology Display. The Vertical Flight Society, 2025. https://doi.org/10.4050/f-0081-2025-60.

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In this study, we employ the Polynomial Chaos Expansion (PCE) and Monte Carlo (MC) methods to quantify the uncertainty of unsteady loading noise generated by a hovering rotor under the presence of vertical gust. The unsteady loading noise is predicted using a frequency-domain approach combined with a quasi-steady Blade Element Momentum Theory, accounting for time-varying aerodynamic forces. A sinusoidal gust is modeled using two parameters: gust length and gust amplitude. Then, the uncertainty quantification (UQ) of the unsteady loading noise is performed using the PCE and MC with these two gu
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Simm, Andrew, Daniel Thomas, Gareth John, and Steve Hodges. "Incorporating Monte Carlo Analysis into a State-of-the-Art Corrosion Prediction System." In CONFERENCE 2023. AMPP, 2023. https://doi.org/10.5006/c2023-18910.

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Abstract The development of corrosion prediction software systems over the years has concentrated on scalar analysis, that is, using fixed input values to develop a single output parameter (corrosion rate). This is consistent with the origins of the majority of prediction systems which are based on the results of a series of laboratory tests using a standard changing variable approach to develop an algorithm providing corrosion rate from the varying inputs. However, it has also been recognised that in real life situations, input parameters are not fixed and also that any algorithm will have a
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Xing, Hailong, WenJie Zhao, and D. H. Li. "Variable Structure Control for Parameter Uncertain Stochastic Systems with Time-Varying Delay." In 2008 IEEE Conference on Robotics, Automation and Mechatronics (RAM). IEEE, 2008. http://dx.doi.org/10.1109/ramech.2008.4681341.

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Mizouri, Hanin, Rihab Lamouchi, and Messaoud Amairi. "Functional Interval Estimation for Uncertain Continuous-time Linear Parameter-Varying Multivariable Systems." In 2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS). IEEE, 2023. http://dx.doi.org/10.1109/iw_mss59200.2023.10369308.

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Southward, Steve C. "Real-Time Parameter ID Using Polynomial Chaos Expansions." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-43745.

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A novel real-time parameter identification algorithm has been developed that exploits polynomial chaos expansion (PCE) representations of uncertain parameters. Dynamic system models inevitably contain parameters whose values are rarely known with absolute certainty. In many cases, such parameters are either not measurable, or they are slowly time varying. In some cases, the dynamic system model is inadequate and parameter values are simply chosen to provide a “best fit” representation. For the method proposed here, we assume apriori knowledge of the probability distributions associated with th
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Cerone, V., and D. Regruto. "Set-membership identification of LPV models with uncertain measurements of the time-varying parameter." In 2008 47th IEEE Conference on Decision and Control. IEEE, 2008. http://dx.doi.org/10.1109/cdc.2008.4739267.

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Li, Shanbin, Dominique Sauter, and Bugong Xu. "Uniformly ultimate boundedness event-triggered control for discrete-time uncertain linear parameter-varying systems." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895920.

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Jun Li, Gang Wu, and Zhiquan Wang. "Robust H&#8734;Fault Tolerant Control Design for Linear Uncertain Systems with Time-varying Norm-bounded Parameter Uncertainty." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1712802.

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Zhang, Zhen, Zongxuan Sun, and Peiqing Ye. "An Internal Model-Based Tracking Control for a Class of Uncertain Linear Time-Varying Systems." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4271.

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In this paper, we extend previous results for a novel internal model-based tracking control with a class of known LTV plant models driven by LTI exosystems to uncertain LTI plant models driven by LTV exosystems. The augmented time-varying system to be stabilized becomes uncertain. Moreover, the time-varying fashion under consideration renders the augmented uncertain system linear parameter-varying (LPV). By means of an output-feedback gain-scheduling design, the augmented uncertain LTV system is stabilized. Simulation results illustrate the proposed design method.
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Reports on the topic "Uncertain time-Varying parameter"

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Hauzenberger, Niko, Florian Huber, Gary Koop, and James Mitchell. Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202305.

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In light of widespread evidence of parameter instability in macroeconomic models, many time-varying parameter (TVP) models have been proposed. This paper proposes a nonparametric TVP-VAR model using Bayesian additive regression trees (BART). The novelty of this model stems from the fact that the law of motion driving the parameters is treated nonparametrically. This leads to great flexibility in the nature and extent of parameter change, both in the conditional mean and in the conditional variance. In contrast to other nonparametric and machine learning methods that are black box, inference us
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Liu and Nixon. L52305 Probabilistic Analysis of Pipeline Uplift Resistance. Pipeline Research Council International, Inc. (PRCI), 2010. http://dx.doi.org/10.55274/r0000002.

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To investigate the feasibility of probabilistic analyses of the peak uplift resistance in frozen soils by varying parameters that are known to be important for the development of the uplift resistance under the upward movement of a pipe. A buried pipeline will be subjected to a variety of forces, both internal and external, including the interaction of the pipe with the surrounding soil. The soil-pipe interaction in permafrost regions have to account for the behavior of frozen and unfrozen soil, and transitions between the two as the pipeline traverses in a discontinuous permafrost zone. The v
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RESIDUAL LIFE PREDICTION AND DESIGN CORRECTION METHOD OF CORRODED CIRCULAR STEEL TUBES BASED ON TIME-VARYING RELIABILITY. The Hong Kong Institute of Steel Construction, 2024. http://dx.doi.org/10.18057/ijasc.2024.20.1.2.

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Current research on the effects of corrosion on the safety of steel members is primarily focused on the degradation of the ultimate bearing capacity, and there is a lack of research on the reliability-based service life assessment. In this paper, a modified reliability function and an uncertainty model for each parameter considering the effects of corrosion are established based on the reliability analysis method of the GB50068-2018 design specification. The effects of the corrosive environment category, wall thickness, and slenderness ratio on the time-varying reliability of axially compresse
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