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Estimation Error (estimation + error)
Terms modified by Estimation Error Selected AbstractsObserver-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] Food energy content influences food portion size estimation by nutrition studentsJOURNAL OF HUMAN NUTRITION & DIETETICS, Issue 3 2010C. C. Japur Abstract Background:, Food portion size estimation involves a complex mental process that may influence food consumption evaluation. Knowing the variables that influence this process can improve the accuracy of dietary assessment. The present study aimed to evaluate the ability of nutrition students to estimate food portions in usual meals and relate food energy content with errors in food portion size estimation. Methods:, Seventy-eight nutrition students, who had already studied food energy content, participated in this cross-sectional study on the estimation of food portions, organised into four meals. The participants estimated the quantity of each food, in grams or millilitres, with the food in view. Estimation errors were quantified, and their magnitude were evaluated. Estimated quantities (EQ) lower than 90% and higher than 110% of the weighed quantity (WQ) were considered to represent underestimation and overestimation, respectively. Correlation between food energy content and error on estimation was analysed by the Spearman correlation, and comparison between the mean EQ and WQ was accomplished by means of the Wilcoxon signed rank test (P < 0.05). Results:, A low percentage of estimates (18.5%) were considered accurate (±10% of the actual weight). The most frequently underestimated food items were cauliflower, lettuce, apple and papaya; the most often overestimated items were milk, margarine and sugar. A significant positive correlation between food energy density and estimation was found (r = 0.8166; P = 0.0002). Conclusions:, The results obtained in the present study revealed a low percentage of acceptable estimations of food portion size by nutrition students, with trends toward overestimation of high-energy food items and underestimation of low-energy items. [source] Parameter estimation accuracy analysis for induction motorsEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 2 2005E. Laroche Abstract Various analytical dynamic models of induction machines, some of which take magnetic saturation and iron loss into account, are available in the literature. When parameter estimation is required, models must not only be theoretically identifiable but allow for accurate parameter estimation as well. This paper presents a comparison of parameter estimation accuracies obtained using different models and sets of measurements in the case of steady-state sinusoidal measurements. An explicit expression of estimation error is established and evaluated with respect to several measurement and modelling errors. This study will show that certain models are better suited for identification purposes than others and that certain sensors are bound to be more accurate than others. Lastly, an optimal experimental design procedure is implemented in order to derive an improved measurement set that leads to reduced estimation errors. Copyright © 2005 John Wiley & Sons, Ltd. [source] Tuning and parameter variation effects in MRAS based speed estimator for sensorless vector controlled induction motor drivesEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2002M. Wang A frequently applied method of speed-sensorless rotor flux oriented control of induction machines relies on utilisation of model reference adaptive system (MRAS) based speed estimation, where the outputs of the reference and the adjustable model are selected as rotor flux space phasors. Accuracy of the method heavily depends on correct setting of the machine parameters and adjustment of the filter and Pl controller parameters within the estimator. The paper at first describes tuning of various parameters of the estimator, using purely experimental data. The speed estimator is operated in parallel with a commercially available rotor flux oriented induction motor drive with speed sensor and sampled stator voltages and currents are used to tune induction motor parameters, various filters and the Pl controller within the estimator. The procedure is described and illustrated using a comparison between the measured actual speed response during acceleration transients and the corresponding speed estimate obtained from the speed estimator. In the second part of the paper, speed estimation error that will take place in the base speed region due to incorrect setting and/or variation of the parameters of the machine (stator resistance, rotor resistance and magnetising inductance) within the speed estimator is assessed using experimentally recorded data. The experimental results are found to be in very good agreement with previously published theoretical results. [source] TESTING LONG-HORIZON PREDICTIVE ABILITY WITH HIGH PERSISTENCE, AND THE MEESE,ROGOFF PUZZLE*INTERNATIONAL ECONOMIC REVIEW, Issue 1 2005Barbara Rossi A well-known puzzle in international finance is that a random walk predicts exchange rates better than economic models. I offer a potential explanation. When exchange rates and fundamentals are highly persistent, long-horizon forecasts of economic models are biased by the estimation error. When this bias is big, a random walk will forecast better, even if the economic model is true. I propose a test for equal predictability in the presence of high persistence. It shows that the poor forecasting ability of economic models does not imply that the models are not good descriptions of the data. [source] Approximate channel identification via , -signed correlationINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 4 2002J. Balakrishnan Abstract A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ,smoothly' from a situation with small sum-squared channel estimation error but hard-to-identify channel peaks, to one with a larger sum-squared estimation error but easy-to-identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd. [source] Estimating missing daily temperature extremes using an optimized regression approachINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 11 2001Robert J. Allen Abstract A variation of a least squares regression approach to estimate missing daily maximum and minimum temperatures is developed and evaluated, specifically for temperature extremes. The method focuses on obtaining accurate estimates of annual exceedence counts (e.g. the number of days greater than or equal to the 90th percentile of daily maximum temperatures), as well as counts of consecutive exceedences, while limiting the estimation error associated with each individual value. The performance of this method is compared with that of two existing methods developed for the entire temperature distribution. In these existing methods, temperature estimates are based on data from neighbouring stations using either regression or temperature departure-based approaches. Evaluation of our approach using cold minimum and warm maximum temperatures shows that the median percentage of correctly identified exceedence counts is 97% and the median percentage of correctly identified consecutive exceedence counts is 98%. The other existing methods tend to underestimate both single and consecutive exceedence counts. Using these procedures, the estimated exceedence counts are generally less than 80% of those that actually occurred. Despite the fact that our method is tuned to estimate exceedence counts, the estimation accuracy of individual daily maximum or minimum temperatures is similar to that of the other estimation procedures. The median absolute error (MAE) using all temperatures greater than or equal to the 90th percentile (T90),1.1°C for ten climatically diverse stations is 1.28°C for our method, while the other methods give MAEs of 1.27 and 1.17°C. In terms of median error, however, the tendency for underprediction by the existing methods is pronounced with ,0.77 and ,0.61°C biases. Our optimized method is relatively unbiased as the resulting mean error is ,0.12°C. Copyright © 2001 Royal Meteorological Society [source] Performance of robust symbol-timing and carrier-frequency estimation for OFDM systemsINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 5 2009Nan-Yang YenArticle first published online: 7 NOV 200 Abstract In recent years, many maximum likelihood (ML) blind estimators have been proposed to estimate timing and frequency offsets for orthogonal frequency division multiplexing (OFDM) systems. However, the previously proposed ML blind estimators utilizing cyclic prefix do not fully characterize the random observation vector over the entire range of the timing offset and will significantly degrade the estimation performance. In this paper, we present a global ML blind estimator to compensate the estimation error. Moreover, we extend the global ML blind estimator by accumulating the ML function of the estimation parameters to achieve a better accuracy without increasing the hardware or computational complexity. The simulation results show that the proposed algorithm can significantly improve the estimation performance in both additional white Gaussian noise and ITU-R M.1225 multipath channels. Copyright © 2008 John Wiley & Sons, Ltd. [source] Predictor-based repetitive learning control for a class of remote control nonlinear systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 16 2007Ya-Jun Pan Abstract In this paper, a repetitive learning control (RLC) approach is proposed for a class of remote control nonlinear systems satisfying the global Lipschitz condition. The proposed approach is to deal with the remote tracking control problem when the environment is periodic or repeatable over infinite time domain. Since there exist time delays in the two transmission channels: from the controller to the actuator and from the sensor to the controller, tracking a desired trajectory through a remote controller is not an easy task. In order to solve the problem caused by time delays, a predictor is designed on the controller side to predict the future state of the nonlinear system based on the delayed measurements from the sensor. The convergence of the estimation error of the predictor is ensured. The gain design of the predictor applies linear matrix inequality (LMI) techniques developed by Lyapunov Kravoskii method for time delay systems. The RLC law is constructed based on the feedback error from the predicted state. The overall tracking error tends to zero asymptotically over iterations. The proof of the stability is based on a constructed Lyapunov function related to the Lyapunov Kravoskii functional used for the proof of the predictor's convergence. By well incorporating the predictor and the RLC controller, the system state tracks the desired trajectory independent of the influence of time delays. A numerical simulation example is shown to verify the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd. [source] Adaptive sensorless robust control of AC drives based on sliding mode control theoryINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 9 2007O. Barambones Abstract This paper focuses in the design of a new adaptive sensorless robust control to improve the trajectory tracking performance of induction motors. The proposed design employs the so-called vector (or field oriented) control theory for the induction motor drives, being the designed control law based on an integral sliding-mode algorithm that overcomes the system uncertainties. This sliding-mode control law incorporates an adaptive switching gain in order to avoid the need of calculating an upper limit for the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first-order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. The simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances. Finally, experimental results show the performance of the proposed control scheme. Copyright © 2006 John Wiley & Sons, Ltd. [source] Delay-dependent fault estimation for uncertain time-delay nonlinear systems: an LMI approachINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 18 2006Sing Kiong Nguang Abstract This paper deals with the problem of robust fault estimation for uncertain time-delay Takagi,Sugeno (TS) fuzzy models. The aim of this study is to design a delay-dependent fault estimator ensuring a prescribed ,, performance level for the fault estimation error, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of a robust fault estimator are given in terms of linear matrix inequalities (LMIs). Membership functions' (MFs) characteristics are incorporated into the fault estimator design to reduce the conservativeness of neglecting these characteristics. Finally, a numerical example is given to illustrate the effectiveness of the proposed design techniques. Copyright © 2006 John Wiley & Sons, Ltd. [source] ,, filtering for discrete-time linear systems with Markovian jumping parameters,,INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2003Carlos E. de Souza Abstract This paper investigates the problem of ,, filtering for discrete-time linear systems with Markovian jumping parameters. It is assumed that the jumping parameter is available. This paper develops necessary and sufficient conditions for designing a discrete-time Markovian jump linear filter which ensures a prescribed bound on the ,2 -induced gain from the noise signals to the estimation error. The proposed filter design is given in terms of linear matrix inequalities. Copyright © 2003 John Wiley & Sons, Ltd. [source] Robust H2 filtering of linear systems with time delaysINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 10 2003E. Fridman Abstract The problem of robust H2 estimation of a combination of states of a stationary linear system with time delays is considered. Since the problem is infinite dimensional in nature, an attempt is being made to develop finite dimensional methods that will guarantee a preassigned estimation accuracy. The approach of minimizing the trace of a matrix that overbounds the exact covariance of the estimation error is considered. Sufficient conditions are given in the form of linear matrix inequalities (LMIs). The results are illustrated by a numerical example. Copyright © 2003 John Wiley & Sons, Ltd. [source] Robust ,, filtering for uncertain Markovian jump linear systems,INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 5 2002Carlos E. de Souza Abstract This paper investigates the problem of ,, filtering for a class of uncertain Markovian jump linear systems. The uncertainty is assumed to be norm-bounded and appears in all the matrices of the system state-space model, including the coefficient matrices of the noise signals. It is also assumed that the jumping parameter is available. We develop a methodology for designing a Markovian jump linear filter that ensures a prescribed bound on the ,2 -induced gain from the noise signals to the estimation error, irrespective of the uncertainty. The proposed design is given in terms of linear matrix inequalities. Copyright © 2002 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] Iterative interference cancellation and channel estimation in multibeam satellite systemsINTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING, Issue 3 2007J. P. Millerioux Abstract This paper deals with the use of non-linear multiuser detection techniques to mitigate co-channel interference on the reverse link of multibeam satellite systems. These techniques allow more capacity efficient frequency reuse strategies than classical ones, as they make possible to cope with lower C/I. The considered system takes as a starting point the DVB-RCS standard, with the use of convolutional coding, and the use of the Ka-band. We propose different iterative interference cancellation schemes, which operate at the beamformer outputs, and which use information from decoders. The proposed receivers assume an initial single-user synchronization step: frame synchronization and timing recovery, and then perform channel estimation: beamformer coefficients; signal carrier phases and signal amplitudes. In a first step, these receivers are evaluated by simulation in terms of bit error rate and of channel estimation error on two interference configurations. For one of these receivers, sensitivity to imperfect timing recovery and to low-frequency offsets from user terminals is evaluated. In a second step, since the receiver performances highly depend on the interference configuration, we propose an approach to evaluate performances on a multibeam coverage (by taking into account the variability of interference configurations on the coverage). This method is used to compare different receivers on an example based on a coverage designed on a digital focal array feed reflector antenna. Copyright © 2007 John Wiley & Sons, Ltd. [source] Separation, optimization, miniaturization and signal space.JOURNAL OF CHEMOMETRICS, Issue 4 2009Optimum measurability factors in process analytical chromatography Abstract The theory concerning optimum separation conditions with respect to the precision and minimum peak estimation error is extended with the derivation of the conditions for optimum measurability in case of chemical process control, resulting in extremely short columns to be used. High-speed correlation chromatography (CC) with a special input device is suggested as a solution for the practical problems of these required columns. An example of a one-second correlogram with a spark modulation input device is shown. An alternative is monitoring chemical processes by multiple input chromatography, applying a polynomial fit procedure. Copyright © 2009 John Wiley & Sons, Ltd. [source] Correction of a bootstrap approach to testing for evolution along lines of least resistanceJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 12 2009D. BERNER Abstract Testing for an association between the leading vectors of multivariate trait (co)variation within populations (the ,line of least resistance') and among populations is an important tool for exploring variational bias in evolution. In a recent study of stickleback fish populations, a bootstrap-based test was introduced that takes into account estimation error in both vectors and hence improves the previously available bootstrap method. Because this test was implemented incorrectly, however, I here describe the correct test protocol and provide a reanalysis of the original data set. The application of this new test protocol should improve future investigations of evolution along lines of least resistance and other vector comparisons. [source] Effect of sampling interval and temperature on the accuracy of food consumption estimates from stomach contentsJOURNAL OF FISH BIOLOGY, Issue 1 2005A. G. Finstad The effect of temperature and sampling interval on the accuracy of food consumption estimates based on stomach contents was studied using simulation. Three temporal patterns of feeding were considered (scattered throughout the day, one 5 h period or two 5 h periods) and gastric evacuation was modelled according to published values. Sampling intervals of 3 h gave reasonable food consumption estimates (2 to 19% error) at all temperatures. Comparably, sampling intervals as large as 12 h gave reasonable estimates of food consumption (1 to 20% error) when temperature was set to ,10° C. At temperatures <5° C, even 24 h intervals (equivalent to one daily sampling) provided reasonable estimates of daily food consumption (2 to 19% error) for all but the highest gastric evacuation rate combined with one daily feeding period (47% error). The temperature effect on estimation error resulted from diminishing temporal fluctuations in stomach contents with slower gastric evacuation rates. It follows that sampling effort may be considerably minimized when estimating food consumption from stomach contents during periods with low temperatures such as the winter time experienced by temperate fishes. [source] STOCK LIQUIDATION VIA STOCHASTIC APPROXIMATION USING NASDAQ DAILY AND INTRA-DAY DATAMATHEMATICAL FINANCE, Issue 1 2006G. Yin By focusing on computational aspects, this work is concerned with numerical methods for stock selling decision using stochastic approximation methods. Concentrating on the class of decisions depending on threshold values, an optimal stopping problem is converted to a parametric stochastic optimization problem. The algorithms are model free and are easily implementable on-line. Convergence of the algorithms is established, second moment bound of estimation error is obtained, and escape probability from a neighborhood of the true parameter is also derived. Numerical examples using both daily closing prices and intra-day data are provided to demonstrate the performance of the algorithms. [source] A note on penalized minimum distance estimation in nonparametric regressionTHE CANADIAN JOURNAL OF STATISTICS, Issue 3 2003Florentina Bunea Abstract The authors introduce a penalized minimum distance regression estimator. They show the estimator to balance, among a sequence of nested models of increasing complexity, the L1 -approximation error of each model class and a penalty term which reflects the richness of each model and serves as a upper bound for the estimation error. Les auteurs présentent un nouvel estimateur de régression obtenu par minimisation d'une distance pénalisée. Ils montrent que pour une suite de modèles embo,tés à complexité croissante, cet estimateur offre un bon compromis entre l'erreur d'approximation L1 de chaque classe de modèles et un terme de pénalisation permettant à la fois de refléter la richesse de chaque modèle et de majorer l'erreur d'estimation. [source] Model error and sequential data assimilation: A deterministic formulationTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 634 2008A. Carrassi Abstract Data assimilation schemes are confronted with the presence of model errors arising from the imperfect description of atmospheric dynamics. These errors are usually modelled on the basis of simple assumptions such as bias, white noise, and first-order Markov process. In the present work, a formulation of the sequential extended Kalman filter is proposed, based on recent findings on the universal deterministic behaviour of model errors in marked contrast with previous approaches. This new scheme is applied in the context of a spatially distributed system proposed by Lorenz. First, it is found that, for short times, the estimation error is accurately approximated by an evolution law in which the variance of the model error (assumed to be a deterministic process) evolves according to a quadratic law, in agreement with the theory. Moreover, the correlation with the initial condition error appears to play a secondary role in the short-time dynamics of the estimation error covariance. Second, the deterministic description of the model error evolution, incorporated into the classical extended Kalman filter equations, reveals that substantial improvements of the filter accuracy can be gained compared with the classical white-noise assumption. The universal short-time quadratic law for the evolution of the model error covariance matrix seems very promising for modelling estimation error dynamics in sequential data assimilation. Copyright © 2008 Royal Meteorological Society [source] Combining state estimator and disturbance observer in discrete-time sliding mode controller design,ASIAN JOURNAL OF CONTROL, Issue 5 2008Jeang-Lin Chang Abstract In response to a multiple input/multiple output discrete-time linear system with mismatched disturbances, an algorithm capable of performing estimated system states and unknown disturbances is proposed first, and then followed with the design of the controller. Attributed to the fact that both system states and disturbances can be estimated simultaneously with our proposed method, the estimation error is constrained at less than O(T) as the disturbance between the two sampling points is insignificant. In addition, the estimated system states and disturbances are then to be used in the controller when implementing our algorithm in a non-minimum phase system (with respect to the relation between the output and the disturbance). The tracking error is constrained in a small bounded region and the system stability is guaranteed. Finally, a numerical example is presented to demonstrate the applicability of the proposed control scheme. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] A GRADIENT BASED ADAPTIVE CONTROL ALGORITHM FOR DUAL-RATE SYSTEMSASIAN JOURNAL OF CONTROL, Issue 4 2006Feng Ding ABSTRACT In this paper, using a polynomial transformation technique, we derive a mathematical model for dual-rate systems. Based on this model, we use a stochastic gradient algorithm to estimate unknown parameters directly from the dual-rate input-output data, and then establish an adaptive control algorithm for dual-rate systems. We prove that the parameter estimation error converges to zero under persistent excitation, and the parameter estimation based control algorithm can achieve virtually asymptotically optimal control and ensure the closed-loop systems to be stable and globally convergent. The simulation results are included. [source] RANDOM APPROXIMATED GREEDY SEARCH FOR FEATURE SUBSET SELECTIONASIAN JOURNAL OF CONTROL, Issue 3 2004Feng Gao ABSTRACT We propose a sequential approach called Random Approximated Greedy Search (RAGS) in this paper and apply it to the feature subset selection for regression. It is an extension of GRASP/Super-heuristics approach to complex stochastic combinatorial optimization problems, where performance estimation is very expensive. The key points of RAGS are from the methodology of Ordinal Optimization (OO). We soften the goal and define success as good enough but not necessarily optimal. In this way, we use more crude estimation model, and treat the performance estimation error as randomness, so it can provide random perturbations mandated by the GRASP/Super-heuristics approach directly and save a lot of computation effort at the same time. By the multiple independent running of RAGS, we show that we obtain better solutions than standard greedy search under the comparable computation effort. [source] Parameter estimation accuracy analysis for induction motorsEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 2 2005E. Laroche Abstract Various analytical dynamic models of induction machines, some of which take magnetic saturation and iron loss into account, are available in the literature. When parameter estimation is required, models must not only be theoretically identifiable but allow for accurate parameter estimation as well. This paper presents a comparison of parameter estimation accuracies obtained using different models and sets of measurements in the case of steady-state sinusoidal measurements. An explicit expression of estimation error is established and evaluated with respect to several measurement and modelling errors. This study will show that certain models are better suited for identification purposes than others and that certain sensors are bound to be more accurate than others. Lastly, an optimal experimental design procedure is implemented in order to derive an improved measurement set that leads to reduced estimation errors. Copyright © 2005 John Wiley & Sons, Ltd. [source] Audit committees and earnings qualityACCOUNTING & FINANCE, Issue 2 2009Peter Baxter G30; G38; M41 Abstract This research investigates whether audit committees are associated with improved earnings quality for a sample of Australian listed companies prior to the introduction of mandatory audit committee requirements in 2003. Two measures of earnings quality are used based on models first developed by Jones (1991) and Dechow and Dichev (2002). Our results indicate that formation of an audit committee reduces intentional earnings management but not accrual estimation errors. We also find differences in the associations between audit committee accounting expertise and the two earnings quality measures. Other audit committee characteristics examined are not significantly related to either earnings quality measure. [source] Estimating soil carbon fluxes following land-cover change: a test of some critical assumptions for a region in Costa RicaGLOBAL CHANGE BIOLOGY, Issue 2 2004Jennifer S. Powers Abstract Changes in soil carbon storage that accompany land-cover change may have significant effects on the global carbon cycle. The objective of this work was to examine how assumptions about preconversion soil C storage and the effects of land-cover change influence estimates of regional soil C storage. We applied three models of land-cover change effects to two maps of preconversion soil C in a 140 000 ha area of northeastern Costa Rica. One preconversion soil C map was generated using values assigned to tropical wet forest from the literature, the second used values obtained from extensive field sampling. The first model of land-cover change effects used values that are typically applied in global assessments, the second and third models used field data but differed in how the data were aggregated (one was based on land-cover transitions and one was based on terrain attributes). Changes in regional soil C storage were estimated for each combination of model and preconversion soil C for three time periods defined by geo-referenced land-cover maps. The estimated regional soil C under forest vegetation (to 0.3 m) was higher in the map based on field data (10.03 Tg C) than in the map based on literature data (8.90 Tg C), although the range of values derived from propagating estimation errors was large (7.67,12.40 Tg C). Regional soil C storage declined through time due to forest clearing for pasture and crops. Estimated CO2 fluxes depended more on the model of land-cover change effects than on preconversion soil C. Cumulative soil C losses (1950,1996) under the literature model of land-cover effects exceeded estimates based on field data by factors of 3.8,8.0. In order to better constrain regional and global-scale assessments of carbon fluxes from soils in the tropics, future research should focus on methods for extrapolating regional-scale constraints on soil C dynamics to larger spatial and temporal scales. [source] Predicting the Tails of Breakthrough Curves in Regional-Scale Alluvial SystemsGROUND WATER, Issue 4 2007Yong Zhang The late tail of the breakthrough curve (BTC) of a conservative tracer in a regional-scale alluvial system is explored using Monte Carlo simulations. The ensemble numerical BTC, for an instantaneous point source injected into the mobile domain, has a heavy late tail transforming from power law to exponential due to a maximum thickness of clayey material. Haggerty et al.'s (2000) multiple-rate mass transfer (MRMT) method is used to predict the numerical late-time BTCs for solutes in the mobile phase. We use a simple analysis of the thicknesses of fine-grained units noted in boring logs to construct the memory function that describes the slow decline of concentrations at very late time. The good fit between the predictions and the numerical results indicates that the late-time BTC can be approximated by a summation of a small number of exponential functions, and its shape depends primarily on the thicknesses and the associated volume fractions of immobile water in "blocks" of fine-grained material. The prediction of the late-time BTC using the MRMT method relies on an estimate of the average advective residence time, tad. The predictions are not sensitive to estimation errors in tad, which can be approximated by , where is the arithmetic mean ground water velocity and L is the transport distance. This is the first example of deriving an analytical MRMT model from measured hydrofacies properties to predict the late-time BTC. The parsimonious model directly and quantitatively relates the observable subsurface heterogeneity to nonlocal transport parameters. [source] An evaluation of sediment rating curves for estimating suspended sediment concentrations for subsequent flux calculations,HYDROLOGICAL PROCESSES, Issue 17 2003Arthur J. Horowitz Abstract In the absence of actual suspended sediment concentration (SSC) measurements, hydrologists have used sediment rating (sediment transport) curves to estimate (predict) SSCs for subsequent flux calculations. Various evaluations of the sediment rating-curve method were made using data from long-term, daily sediment-measuring sites within large (>1 000 000 km2), medium (<1 000 000 to >1000 km2), and small (<1000 km2) river basins in the USA and Europe relative to the estimation of suspended sediment fluxes. The evaluations address such issues as the accuracy of flux estimations for various levels of temporal resolution as well as the impact of sampling frequency on the magnitude of flux estimation errors. The sediment rating-curve method tends to underpredict high, and overpredict low SSCs. As such, the range of errors associated with concomitant flux estimates for relatively short time-frames (e.g. daily, weekly) are likely to be substantially larger than those associated with longer time-frames (e.g. quarterly, annually) because the over- and underpredictions do not have sufficient time to balance each other. Hence, when error limits must be kept under ±20%, temporal resolution probably should be limited to quarterly or greater. The evaluations indicate that over periods of 20 or more years, errors of <1% can be achieved using a single sediment rating curve based on data spanning the entire period. However, somewhat better estimates for the entire period, and markedly better annual estimates within the period, can be obtained if individual annual sediment rating curves are used instead. Relatively accurate (errors <±20%) annual suspended sediment fluxes can be obtained from hydrologically based monthly measurements/samples. For 5-year periods or longer, similar results can be obtained from measurements/samples collected once every 2 months. In either case, hydrologically based sampling, as opposed to calendar-based sampling is likely to limit the magnitude of flux estimation errors. Published in 2003 John Wiley & Sons, Ltd. [source] | ||||||||||||||||||||||||||||