Home About us Contact
|
Home About us Contact | ||
|
|
||
Model Uncertainty (model + uncertainty)
Selected AbstractsMODEL UNCERTAINTY AND ITS IMPACT ON THE PRICING OF DERIVATIVE INSTRUMENTSMATHEMATICAL FINANCE, Issue 3 2006Rama Cont Uncertainty on the choice of an option pricing model can lead to "model risk" in the valuation of portfolios of options. After discussing some properties which a quantitative measure of model uncertainty should verify in order to be useful and relevant in the context of risk management of derivative instruments, we introduce a quantitative framework for measuring model uncertainty in the context of derivative pricing. Two methods are proposed: the first method is based on a coherent risk measure compatible with market prices of derivatives, while the second method is based on a convex risk measure. Our measures of model risk lead to a premium for model uncertainty which is comparable to other risk measures and compatible with observations of market prices of a set of benchmark derivatives. Finally, we discuss some implications for the management of "model risk." [source] Robust Maintenance Policies for Markovian Systems under Model UncertaintyCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 3 2006Kenneth D. Kuhn Many sources of error, some difficult to quantify, can limit the ability of asset management systems to accurately predict how built systems will deteriorate. This article introduces the use of robust optimization to deal with epistemic uncertainty. The Hurwicz criterion is employed to ensure management policies are never "too conservative." An efficient solution algorithm is developed to solve robust counterparts of the asset management problem. A case study demonstrates how the consideration of uncertainty alters optimal management policies and shows how the proposed approach may reduce maintenance and rehabilitation (M&R) expenditures. [source] Vadose Zone Flow Model Uncertainty as Conditioned on Geophysical DataGROUND WATER, Issue 2 2003Andrew Binley An approach to estimating the uncertainty in model descriptions based on a landscape space to model space mapping concept is described. The approach is illustrated by an application making use of plot scale geophysical estimates of changes in water content profiles to condition a model of recharge to the Sherwood Sandstone Aquifer in the United Kingdom. It is demonstrated that the mapping is highly uncertain and that many different parameter sets give acceptable simulations of the observations. Multiple profile measurements over time offer only limited additional constraints on the mapping. The resulting mapping weights may be used to evaluate uncertainty in the predictions of vadose zone flow dynamics for the site. [source] Forecasting Substantial Data Revisions in the Presence of Model Uncertainty,THE ECONOMIC JOURNAL, Issue 530 2008Anthony Garratt A recent revision to the preliminary measurement of GDP(E) growth for 2003Q2 caused considerable press attention, provoked a public enquiry and prompted a number of reforms to UK statistical reporting procedures. In this article, we compute the probability of ,substantial revisions' that are greater (in absolute value) than the controversial 2003 revision. The predictive densities are derived from Bayesian model averaging over a wide set of forecasting models including linear, structural break and regime-switching models with and without heteroscedasticity. Ignoring the nonlinearities and model uncertainty yields misleading predictives and obscures recent improvements in the quality of preliminary UK macroeconomic measurements. [source] Nonparametric probabilistic approach of uncertainties for elliptic boundary value problemINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 6-7 2009Christian SoizeArticle first published online: 2 FEB 200 Abstract The paper is devoted to elliptic boundary value problems with uncertainties. Such a problem has already been analyzed in the context of the parametric probabilistic approach of system parameters uncertainties or for random media. Model uncertainties are induced by the mathematical,physical process, which allows the boundary value problem to be constructed from the design system. If experiments are not available, the Bayesian approach cannot be used to take into account model uncertainties. Recently, a nonparametric probabilistic approach of both the model uncertainties and system parameters uncertainties has been proposed by the author to analyze uncertain linear and non-linear dynamical systems. Nevertheless, the use of this concept that has to be developed for dynamical systems cannot directly be applied for elliptic boundary value problem, for instance, for a linear elastostatic problem relative to an elastic bounded domain. We then propose an extension of the nonparametric probabilistic approach in order to take into account model uncertainties for strictly elliptic boundary value problems. The theory and its validation are presented. Copyright © 2009 John Wiley & Sons, Ltd. [source] The effect of the 19F(,, p)22Ne reaction rate uncertainty on the yield of fluorine from Wolf,Rayet starsMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2005Richard J. Stancliffe ABSTRACT In the light of recent recalculations of the 19F(,, p)22Ne reaction rate, we present results of the expected yield of 19F from Wolf,Rayet (WR) stars. In addition to using the recommended rate, we have computed models using the upper and lower limits for the rate, and hence we constrain the uncertainty in the yield with respect to this reaction. We find a yield of 3.1 × 10,4 M, of 19F with our recommended rate, and a difference of a factor of 2 between the yields computed with the upper and lower limits. In comparison with previous work we find a difference in the yield of a factor of approximately 4, connected with a different choice of mass loss. Model uncertainties must be carefully evaluated in order to obtain a reliable estimate of the yield, together with its uncertainties, of fluorine from WR stars. [source] A one-dimensional model for simulating armouring and erosion on hillslopes: 2.EARTH SURFACE PROCESSES AND LANDFORMS, Issue 10 2007Long term erosion, armouring predictions for two contrasting mine spoils Abstract This paper investigates the dynamics of soil armouring as a result of fluvial erosion for a non-cohesive sandy gravel spoil from the Ranger Mine, Australia, and a cohesive silt loam spoil from the Northparkes Mine, Australia, using a model for hillslope soil armouring. These long term predictions concentrate on the temporal and spatial changes of the spoil grading and erosion over 100,200 years for the flat cap regions (1,2%) and steep batter edges (10,30%) typically encountered on waste rock dumps. The existence of a significant rock fragment fraction in the Ranger spoil means that it armours readily, while Northparkes does not. For Ranger the waste rock showed reductions in (1) cumulative erosion of up to 81% from that obtained by extrapolating the initial erosion rate out 100 years and (2) the erosion/year by more than 10-fold. For Northparkes reductions were less marked, with the maximum reduction in erosion/year being 37% after 200 years. For Ranger the reductions were greatest and fastest for intermediate gradient hillslopes. For the steepest hillslopes the armouring decreased because the flow shear stresses were large enough to mobilize all material in the armour layer. Model uncertainty was assessed with probabilistic confidence limits demonstrating that these erodibility reductions were statistically significant. A commonly used hillslope erosion model (sediment flux = ,1 discharge m1 slope n1) was fitted to these predictions. The erodibility, ,1, and m1 decreased with time, which was consistent with our physical intuition about armouring. At Ranger the parameter m1 asymptoted to 1·5,1·6 while at Northparkes it asymptoted to 1·2,1·3. At Ranger transient spatial trends in armouring led to a short term (50,200 years in the future) reduction in n1, to below zero under certain circumstances, recovering to an asymptote of about 0·5,1. At Northparkes n1 asymptoted to about 0·6, with no negative transients predicted. The m1 and n1 parameters predicted for Ranger were shown to be consistent with field data from a 10-year-old armoured hillslope and consistent with published relationships between erodibility and rock content for natural hillslopes. Copyright © 2007 John Wiley & Sons, Ltd. [source] Bayesian uncertainty assessment in multicompartment deterministic simulation models for environmental risk assessmentENVIRONMETRICS, Issue 4 2003Samantha C. Bates Abstract We use a special case of Bayesian melding to make inference from deterministic models while accounting for uncertainty in the inputs to the model. The method uses all available information, based on both data and expert knowledge, and extends current methods of ,uncertainty analysis' by updating models using available data. We extend the methodology for use with sequential multicompartment models. We present an application of these methods to deterministic models for concentration of polychlorinated biphenyl (PCB) in soil and vegetables. The results are posterior distributions of concentration in soil and vegetables which account for all available evidence and uncertainty. Model uncertainty is not considered. Copyright © 2003 John Wiley & Sons, Ltd. [source] Model uncertainty in the ecosystem approach to fisheriesFISH AND FISHERIES, Issue 4 2007Simeon L. Hill Abstract Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure, an issue of increasing importance as ecosystem models are devised to support the move to an ecosystem approach to fisheries (EAF). This paper sets out pragmatic approaches with which to account for uncertainties in model structure and we review current ways of dealing with this issue in fisheries and other disciplines. All involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be asked to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalize hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of an EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in ways that represent the risks and trade-offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, and a dialogue among fisheries modellers and modellers from other scientific communities will therefore be helpful. [source] Introduction: ,Model uncertainty and macroeconomics'JOURNAL OF APPLIED ECONOMETRICS, Issue 1 2010Steven N. Durlauf No abstract is available for this article. [source] Model uncertainty in cross-country growth regressionsJOURNAL OF APPLIED ECONOMETRICS, Issue 5 2001Carmen Fernández We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast to Levine and Renelt (1992), our results broadly support the more ,optimistic' conclusion of Sala-i-Martin (1997b), namely that some variables are important regressors for explaining cross-country growth patterns. However, care should be taken in the methodology employed. The approach proposed here is firmly grounded in statistical theory and immediately leads to posterior and predictive inference. Copyright © 2001 John Wiley & Sons, Ltd. [source] New approaches to understanding late Quaternary climate fluctuations and refugial dynamics in Australian wet tropical rain forestsJOURNAL OF BIOGEOGRAPHY, Issue 2 2009Jeremy VanDerWal Abstract Aim, We created spatially explicit models of palaeovegetation stability for the rain forests of the Australia Wet Tropics. We accounted for the climatic fluctuations of the late Quaternary, improving upon previous palaeovegetation modelling for the region in terms of data, approach and coverage of predictions. Location, Australian Wet Tropics. Methods, We generated climate-based distribution models for broad rain forest vegetation types using contemporary and reconstructed ,pre-clearing' vegetation data. Models were projected onto previously published palaeoclimate scenarios dating to c. 18 kyr bp. Vegetation stability was estimated as the average likelihood that a location was suitable for rain forest through all climate scenarios. Uncertainty associated with model projections onto novel environmental conditions was also tracked. Results, Upland rain forest was found to be the most stable of the wet forest vegetation types examined. We provide evidence that the lowland rain forests were largely extirpated from the region during the last glacial maximum, with only small, marginally suitable fragments persisting in two areas. Models generated using contemporary vegetation data underestimated the area of environmental space suitable for rain forest in historical time periods. Model uncertainty resulting from projection onto novel environmental conditions was low, but generally increased with the number of years before present being modelled. Main conclusions, Climate fluctuations of the late Quaternary probably resulted in dramatic change in the extent of rain forest in the region. Pockets of high-stability upland rain forest were identified, but extreme bottlenecks of area were predicted for lowland rain forest. These factors are expected to have had a dramatic impact on the historical dynamics of population connectivity and patterns of extinction and recolonization of dependent fauna. Finally, we found that models trained on contemporary vegetation data can be problematic for reconstructing vegetation patterns under novel environmental conditions. Climatic tolerances and the historical extent of vegetation may be underestimated when artificial vegetation boundaries imposed by land clearing are not taken into account. [source] Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgetsEARTH SURFACE PROCESSES AND LANDFORMS, Issue 2 2010Joseph M. Wheaton Abstract Repeat topographic surveys are increasingly becoming more affordable, and possible at higher spatial resolutions and over greater spatial extents. Digital elevation models (DEMs) built from such surveys can be used to produce DEM of Difference (DoD) maps and estimate the net change in storage terms for morphological sediment budgets. While these products are extremely useful for monitoring and geomorphic interpretation, data and model uncertainties render them prone to misinterpretation. Two new methods are presented, which allow for more robust and spatially variable estimation of DEM uncertainties and propagate these forward to evaluate the consequences for estimates of geomorphic change. The first relies on a fuzzy inference system to estimate the spatial variability of elevation uncertainty in individual DEMs while the second approach modifies this estimate on the basis of the spatial coherence of erosion and deposition units. Both techniques allow for probabilistic representation of uncertainty on a cell-by-cell basis and thresholding of the sediment budget at a user-specified confidence interval. The application of these new techniques is illustrated with 5 years of high resolution survey data from a 1,km long braided reach of the River Feshie in the Highlands of Scotland. The reach was found to be consistently degradational, with between 570 and 1970,m3 of net erosion per annum, despite the fact that spatially, deposition covered more surface area than erosion. In the two wetter periods with extensive braid-plain inundation, the uncertainty analysis thresholded at a 95% confidence interval resulted in a larger percentage (57% for 2004,2005 and 59% for 2006,2007) of volumetric change being excluded from the budget than the drier years (24% for 2003,2004 and 31% for 2005,2006). For these data, the new uncertainty analysis is generally more conservative volumetrically than a standard spatially-uniform minimum level of detection analysis, but also produces more plausible and physically meaningful results. The tools are packaged in a wizard-driven Matlab software application available for download with this paper, and can be calibrated and extended for application to any topographic point cloud (x,y,z). Copyright © 2009 John Wiley & Sons, Ltd. [source] Larval lobster (Homarus americanus) distribution and drift in the vicinity of the Gulf of Maine offshore banks and their probable originsFISHERIES OCEANOGRAPHY, Issue 2 2005G. C. HARDING Abstract Surveys for lobster larvae in offshore waters of the north-eastern Gulf of Maine in 1983, 1987 and 1989 confirm that local hatching occurs mainly at depths <100 m over the banks, including Georges and Browns Banks. Detailed studies in the vicinity of Georges Bank in late July of both 1987 and 1989 indicate that the first and second moult stages were located primarily over the bank whereas stages III and IV lobster were collected both over and off the bank. At times stage IV lobster were more abundant off the bank than over it. The condition of stage III and IV lobster, as measured by a lipid index, was better off than over Georges Bank in 1988 and 1989 indicating a possible physiological advantage to being off the bank. In addition, the higher surface temperatures off Georges Bank would shorten larval development time to settlement. To determine the probable hatch sites of stage IV lobster collected off of Browns Bank in 1983 and off of Georges in 1987 and 1989, a 3-D circulation model of the Gulf of Maine was used to simulate larval lobster drift backwards in time. In all cases, areas off Cape Cod, MA, and off Penobscot Bay, ME were suggested as the source of the larvae, although most of the larval trajectories never reached these near-shore waters that are well-known, larval hatching areas. The model-projected larval release times match most closely the observed inshore hatch off Massachusetts but model uncertainties mean that coastal Maine cannot be ruled out as a source. Georges Bank is also a potential source because the present model does not take into account short-term wind events, off-bank eddy transport or the possibility of directed off-bank larval swimming. Examination of weather records prior to and during our 1988 and 1989 sampling periods indicates that winds were not of sufficient intensity and duration to induce larval transport off Georges Bank. The shedding of eddies from the northern flank of Georges Bank into the Gulf of Maine are a relatively common phenomenon during summer but not enough is known about them to evaluate their contribution to possible cross-bank transport of lobster larvae. Directed larval swimming is another possible source for the stage IV lobster found near Georges Bank. Plankton distributions across the northern frontal zone of Georges Bank in 1988 were used as proxies for the scarce larval lobsters. The more surface distribution of the microplankton, in particular, supports the possibility that wind and eddy events may be important in the transport of stage III and IV lobsters off of Georges Bank. Further studies are needed to evaluate these possible additional sources of advanced stage lobster larvae found off of the offshore banks. [source] Spatially distributed observations in constraining inundation modelling uncertaintiesHYDROLOGICAL PROCESSES, Issue 16 2005Micha Werner Abstract The performance of two modelling approaches for predicting floodplain inundation is tested using observed flood extent and 26 distributed floodplain level observations for the 1997 flood event in the town of Usti nad Orlici in the Czech Republic. Although the one-dimensional hydrodynamic model and the integrated one- and two-dimensional model are shown to perform comparably against the flood extent data, the latter shows better performance against the distributed level observations. Comparable performance in predicting the extent of inundation is found to be primarily as a result of the urban reach considered, with flood extent constrained by road and railway embankments. Uncertainty in the elevation model used in both approaches is shown to have little effect on the reliability in predicting flood extent, with a greater impact on the ability in predicting the distributed level observations. These results show that reliability of flood inundation modelling in urban reaches, where flood risk assessment is of more interest than in more rural reaches, can be improved greatly if distributed observations of levels in the floodplain are used in constraining model uncertainties. Copyright © 2005 John Wiley & Sons, Ltd. [source] Nonparametric probabilistic approach of uncertainties for elliptic boundary value problemINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 6-7 2009Christian SoizeArticle first published online: 2 FEB 200 Abstract The paper is devoted to elliptic boundary value problems with uncertainties. Such a problem has already been analyzed in the context of the parametric probabilistic approach of system parameters uncertainties or for random media. Model uncertainties are induced by the mathematical,physical process, which allows the boundary value problem to be constructed from the design system. If experiments are not available, the Bayesian approach cannot be used to take into account model uncertainties. Recently, a nonparametric probabilistic approach of both the model uncertainties and system parameters uncertainties has been proposed by the author to analyze uncertain linear and non-linear dynamical systems. Nevertheless, the use of this concept that has to be developed for dynamical systems cannot directly be applied for elliptic boundary value problem, for instance, for a linear elastostatic problem relative to an elastic bounded domain. We then propose an extension of the nonparametric probabilistic approach in order to take into account model uncertainties for strictly elliptic boundary value problems. The theory and its validation are presented. Copyright © 2009 John Wiley & Sons, Ltd. [source] Performance analysis of a variable structure controller for power regulation of WECS operating in the stall regionINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 15 2001H. De Battista Abstract This paper deals with power regulation in variable speed wind energy conversion systems. The importance of power control in the stall region is stressed. This mode of operation is characterized by a non-minimum phase behaviour. A variable structure controller is described that provides stability by means of speed feedback and is robust to grid disturbances and model uncertainties. Performance of the controller is investigated. A compromise arises in the design of the speed feedback gain between high and low frequency wind components rejection. Furthermore, a cut-off frequency of the wind velocity measurement is obtained that minimizes the effect of turbulence on power regulation. Simulation results are presented, corroborating the features of the control strategy. Copyright © 2001 John Wiley & Sons, Ltd. [source] Robust feedforward design in the presence of LTI/LTV uncertaintiesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2007Gilles Ferreres Abstract A practical method is proposed for the convex design of robust feedforward controllers which ensures H,/L2 performance in the face of LTI and arbitrarily time-varying model uncertainties. A technique that computes the global minimum of this difficult infinite dimensional optimization problem is proposed, as well as a suboptimal but computationally less involved algorithm. Convergence is proved. An efficient way to analyse the robustness properties of a closed loop with or without feedforward controller is obtained as a subproblem. A missile example illustrates the efficiency of the scheme: a robust feedforward controller is designed either on the continuum of linearized time-invariant models (corresponding to trim points) or on a quasi-LPV model representing the non-linear one. Copyright © 2007 John Wiley & Sons, Ltd. [source] A new non-linear sliding-mode torque and flux control method for an induction machine incorporating a sliding-mode flux observerINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 5 2004Fang Chen Abstract In this paper a novel sliding-mode control algorithm, based on the differential geometry state-co-ordinates transformation method, is proposed to control motor torque directly. Non-linear feedback linearization theory is employed to decouple the control of rotor flux magnitude and motor torque. The advantages of this method are: (1) The rotor flux and the generated torque can be accurately controlled. (2) Robustness with respect to matched and mismatched uncertainties is obtained. Additionally, a varying continuous control term is proposed. As a result, chattering is eliminated without sacrificing robustness and precision. The control strategy is based on all motor states being available. In practice the rotor fluxes are not usually measurable, and a sliding-mode observer is derived to estimate the rotor flux. The observer is designed to possess invariant dynamic modes which can be assigned independently to achieve the desired performance. Furthermore, it can be shown that the observer is robust against model uncertainties and measurement noise. Simulation and practical results are presented to confirm the characteristics of the proposed control law and rotor flux observer. Copyright © 2004 John Wiley & Sons, Ltd. [source] Reduction of dynamic LFT systems with LTI model uncertaintiesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 3 2004Gilles FerreresArticle first published online: 6 JAN 200 Abstract A method was proposed by Beck et al. (IEEE Trans Automatic Control, 1996; 41: 1466,1477), for reducing an LFT system with linear time varying model uncertainties. This paper extends this method to the case of linear time invariant model uncertainties, by computing on a finite frequency interval frequency-dependent generalized grammians. The original method by Beck et al. is proved to be equivalent to the computation of constant generalized grammians on the infinite frequency interval (,,,+,). Copyright © 2004 John Wiley & Sons, Ltd. [source] Fault estimation,a standard problem approachINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 8 2002J. Stoustrup This paper presents a range of optimization based approaches to fault diagnosis. A variety of fault diagnosis problems are reformulated in the so-called standard problem set-up introduced in the literature on robust control. Once the standard problem formulations are given, the fault diagnosis problems can be solved by standard optimization techniques. The proposed methods include (1) fault diagnosis (fault estimation, (FE)) for systems with model uncertainties; FE for systems with parametric faults, and FE for a class of nonlinear systems. Copyright © 2002 John Wiley & Sons, Ltd. [source] Observer-based adaptive robust control of a class of nonlinear systems with dynamic uncertainties,INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 4 2001Bin Yao Abstract In this paper, a discontinuous projection-based adaptive robust control (ARC) scheme is constructed for a class of nonlinear systems in an extended semi-strict feedback form by incorporating a nonlinear observer and a dynamic normalization signal. The form allows for parametric uncertainties, uncertain nonlinearities, and dynamic uncertainties. The unmeasured states associated with the dynamic uncertainties are assumed to enter the system equations in an affine fashion. A novel nonlinear observer is first constructed to estimate the unmeasured states for a less conservative design. Estimation errors of dynamic uncertainties, as well as other model uncertainties, are dealt with effectively via certain robust feedback control terms for a guaranteed robust performance. In contrast with existing conservative robust adaptive control schemes, the proposed ARC method makes full use of the available structural information on the unmeasured state dynamics and the prior knowledge on the bounds of parameter variations for high performance. The resulting ARC controller achieves a prescribed output tracking transient performance and final tracking accuracy in the sense that the upper bound on the absolute value of the output tracking error over entire time-history is given and related to certain controller design parameters in a known form. Furthermore, in the absence of uncertain nonlinearities, asymptotic output tracking is also achieved. Copyright © 2001 John Wiley & Sons, Ltd. [source] Inverse filtering and deconvolutionINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 2 2001Ali Saberi Abstract This paper studies the so-called inverse filtering and deconvolution problem from different angles. To start with, both exact and almost deconvolution problems are formulated, and the necessary and sufficient conditions for their solvability are investigated. Exact and almost deconvolution problems seek filters that can estimate the unknown inputs of the given plant or system either exactly or almostly whatever may be the unintended or disturbance inputs such as measurement noise, external disturbances, and model uncertainties that act on the system. As such they require strong solvability conditions. To alleviate this, several optimal and suboptimal deconvolution problems are formulated and studied. These problems seek filters that can estimate the unknown inputs of the given system either exactly, almostly or optimally in the absence of unintended (disturbance) inputs, and on the other hand, in the presence of unintended (disturbance) inputs, they seek that the influence of such disturbances on the estimation error be as small as possible in a certain norm (H2 or H,) sense. Both continuous- and discrete-time systems are considered. For discrete-time systems, the counter parts of all the above problems when an ,,-step delay in estimation is present are introduced and studied. Next, we focus on the exact and almost deconvolution but this time when the uncertainties in plant dynamics can be structurally modeled by a ,-block as a feedback element to the nominally known plant dynamics. This is done either in the presence or absence of external disturbances. Copyright © 2001 John Wiley & Sons, Ltd. [source] Systematic estimation of state noise statistics for extended Kalman filtersAICHE JOURNAL, Issue 2 2000Jaleel Valappil The successful application of model-based control depends on the information about the states of the dynamic system. State-estimation methods, like extended Kalman filters (EKF), are useful for obtaining reliable estimates of the states from a limited number of measurements. They also can handle the model uncertainties and the effect of unmeasured disturbances. The main issue in applying EKF remains that one needs to specify the confidence in the model in terms of process noise covariance matrix. The information about the model uncertainties can effectively and systematically calculate the process noise covariance matrix for an EKF. Two systematic approaches are used for this calculation. The first is based on a Taylor series expansion of the nonlinear equations around the nominal parameter values, while the second accounts for the nonlinear dependence of the system on the fitted parameters by Monte Carlo simulations that can easily be performed on-line. The value of the process noise covariance matrix obtained is not limited to a diagonal form and depends on the current state of the dynamic system. Thus the a-priori information regarding the uncertainty in the model is utilized and the need for extensive tuning of the EKF is eliminated. The application of these techniques to example processes is also discussed. The accuracy of this methodology is compared very favorably with the traditional methods of trial-and-error tuning of EKF. [source] The influence of experimental and model uncertainties on EXAFS resultsJOURNAL OF SYNCHROTRON RADIATION, Issue 2 2001Hermann Rossner We analyze EXAFS oscillations in k-space with the FEFF code to obtain main-shell distances R, and mean-square displacement parameters ,i2 for all single and multiple scattering paths i in the shells , up to a maximum shell radius Rmax. To quantify the uncertainty in the determination of these model parameters we take into account experimental errors and uncertainties connected with background subtraction, with the approximate handling of the electronic many-body problem in FEFF, and with the truncation of the multiple scattering series. The impact of these uncertainties on the R, and ,i2 is investigated in the framework of Bayesian methods. We introduce an a priori guess of these model parameters and consider two alternative strategies to control the weight of the a priori input relative to that of the experimental data. We can take a model parameter space of up to 250 dimensions. Optionally we can also fit the coordination numbers Nj (j,,) and the skewness of the distribution of the R, besides the R, and ,i2. The method is applied to 10K Cu K-edge and 300K Au L3 -edge data to obtain model parameters and their a posteriori error correlation matrices. [source] Reanalysis and reforecast of three major European storms of the twentieth century using the ECMWF forecasting system.METEOROLOGICAL APPLICATIONS, Issue 2 2005Part II: Ensemble forecasts In Part II of this study the ECMWF Ensemble Prediction System (EPS) is used to study the probabilistic predictability of three major European storms of the twentieth century. The storms considered are the Dutch storm of 1 February 1953, the Hamburg storm of 17 February 1962, and the British/French storm of October 1987 (Great October storm). Common to all these storms is their severity that caused large loss of life and widespread damage. In Part I of this study it has been found that deterministic predictability of the Dutch and Hamburg storms amount to 48 and 84 hours, respectively. Here, it is shown that the ensemble forecasts supplement the deterministic forecasts. The large number of members in the 48 and 84 hour ensemble forecasts of the Dutch and Hamburg storms, respectively, suggest that at this forecast range and for these storms the sensitivity of the forecasts to analysis and model uncertainties is rather small. From these results, therefore, it is argued that reliable warnings (i.e. low probability for the occurrence of a forecast failure) for the Dutch and Hamburg storms could have been issued 48 and 84 hours, respectively, in advance, had the current ECMWF EPS been available. For the Great October storm it has been found in Part I of this study that short-range and medium-range forecasts of the intensity and track of the storm were very skilful with a high-resolution model of the ECWMF model. The actual timing of the storm, however, was difficult to predict. Here, it is shown that the EPS is capable of predicting large forecast uncertainties associated with the timing of the Great October storm up to 4 days in advance. It is argued that reliable warnings could have been issued at least 96 hours in advance had the ECMWF EPS been available. From the results presented in this study it is concluded that an Ensemble Prediction System is an important component of every early warning system for it allows an a priori quantification of the probability of the occurrence of severe wind storms. Copyright © 2005 Royal Meteorological Society [source] Nonlinear temperature control of a batch suspension polymerization reactorPOLYMER ENGINEERING & SCIENCE, Issue 6 2002Mohammad Shahrokhi This paper concerns nonlinear temperature control of a batch polymerization reactor where suspension polymerization of methyl methacrylate (MMA) takes place. For this purpose, four control algorithms, namely, a fix proportional-integral (PI) controller, an adaptive proportional-integral-derivative (PID) controller and two globally linearizing control (GLC) schemes, one for known kinetic model (GLC-I) and the other for unknown kinetic model (GLC-II), are selected. The performances of these controllers are compared through simulation and real-time studies in the presence of different levels of parameter uncertainty. The results indicate that GLCI and GLC-II have better performances than fix PI and adaptive PID, especially in case of strong gel effect. The worst performance belongs to adaptive PID because of rapid model changes in gel effect region. GLC-II has a simpler structure than GLC-I and can be used without requiring the kinetic model. In implementation of GLC-I the closed loop observer should be used because of model uncertainties. [source] Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine ProgrammeTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 625 2007Evelyne Richard Abstract The improvement of Quantitative Precipitation Forecasting (QPF) in mountainous regions was a major supporting objective of the Mesoscale Alpine Programme (MAP) project P1 devoted to the study of orographic precipitation. This paper reviews the main MAP-related achievements regarding QPF improvement and highlights the MAP impact on developing QPF research and planning future operational strategies. Recent results based on MAP case-studies, on data analysis and assimilation, on quantification of model uncertainties, and on model intercomparison and verification substantiate the progress made in recent years in improving model performance in relation to short-range, high-resolution forecasting in complex topography regions, well represented by the European Alps. Copyright © 2007 Royal Meteorological Society [source] Robust unscented Kalman filtering for nonlinear uncertain systemsASIAN JOURNAL OF CONTROL, Issue 3 2010K. Xiong Abstract A derivative-free robust Kalman filter algorithm is proposed for nonlinear uncertain systems. The unscented transform (UT) is adopted instead of the linearization technique to obtain the solution of the H, filter Riccati equation. A robust unscented Kalman filter (RUKF) is derived to guarantee an optimized upper bound on the estimation error covariance despite the model uncertainties and the approximation error of the UT. The proposed algorithm is applied to a satellite attitude determination system. Simulation results show that the RUKF is more effective than the unscented Kalman filter (UKF) in cases where alignment errors are present. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] AN ITERATIVE LMI APPROACH TO RFDF FOR LINEAR SYSTEM WITH TIME-VARYING DELAYSASIAN JOURNAL OF CONTROL, Issue 1 2006Maiying Zhong ABSTRACT This paper deals with robust fault detection filter (RFDF) problem for a class of linear uncertain systems with time-varying delays and model uncertainties. The RFDF design problem is formulated as an optimization problem by using L2 -induced norm to represent the robustness of residual to unknown inputs and modelling errors, and the sensitivity to faults. A sufficient condition to the solvability of formulated problem is established in terms of certain matrix inequalities, which can be solved with the aid of an iterative linear matrix inequality (ILMI) algorithm. Finally, a numerical example is given to illustrate the effectiveness of the proposed method. [source] | ||||||||||||||||||||||||||||