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Performance Criterion (performance + criterion)
Selected AbstractsAdaptive motion/force tracking control of holonomic constrained mechanical systems: a unified viewpointINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2007Chian-Song Chiu Abstract This paper proposes a robust adaptive motion/force tracking controller for holonomic constrained mechanical systems with parametric uncertainties and disturbances. First, two types of well-known holonomic systems are reformulated as a unified control model. Based on the unified control model, an adaptive scheme is then developed in the presence of pure parametric uncertainty. The proposed controller guarantees asymptotic motion and force tracking without the need of extra conditions. Next, when considering external disturbances, control gains are designed by solving a linear matrix inequality (LMI) problem to achieve prescribed robust performance criterion. Indeed, arbitrary disturbance/parametric error attenuation with respect to both motion and force errors along with control input penalty are ensured in the L2 -gain sense. Finally, applications are carried out on a two-link constrained robot and two planar robots transporting a common object. Numerical simulation results show the expected performances. Copyright © 2006 John Wiley & Sons, Ltd. [source] Parameter landscapes unveil the bias in allometric predictionMETHODS IN ECOLOGY AND EVOLUTION, Issue 1 2010Cang Hui Summary 1. The criteria for choosing the appropriate line-fitting method (LFM) and correction estimator for determining the functional allometric relationship, and for predicting the Y -variable accurately are controversial. A widely accepted criterion for reducing bias in allometric prediction is to minimize the mean squared residual (MSR) on the antilog scale, and a series of correction estimators have been designed precisely to achieve this. 2. Here, using parameter landscapes, we examine the performance of the correction estimators and several LFMs under different data reszidual shapes, sample sizes and coefficients of determination. 3. Predictions from the nonlinear LFM were found to have minimum MSR values (minimum bias), but with obviously skewed frequency distributions of the predicted Y -variable compared with observed data. This implies that using MSR as a bias measure for allometric prediction could be misleading. 4. We introduce a new bias measure, the discrepancy of the frequency distributions of the Y -variable between predicted and observed data, and suggest that the reduced major axis method is the least biased method in most cases, both on the logarithmic and antilog scales. 5. Parameter landscapes clearly illustrate the performance of each LFM and correction estimator, as well as the best solution given specified criteria. We therefore suggest a shift in emphasis from designing more sophisticated LFM or correction estimators (equal to finding the peaks in the parameter landscape) to justifying the measure of bias and performance criterion in allometric prediction. [source] Identification and fine tuning of closed-loop processes under discrete EWMA and PI adjustmentsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 6 2001Rong Pan Abstract Conventional process identification techniques of a open-loop process use the cross-correlation function between historical values of the process input and of the process output. If the process is operated under a linear feedback controller, however, the cross-correlation function has no information on the process transfer function because of the linear dependency of the process input on the output. In this paper, several circumstances where a closed-loop system can be identified by the autocorrelation function of the output are discussed. It is assumed that a proportional integral controller with known parameters is acting on the process while the output data were collected. The disturbance is assumed to be a member of a simple yet useful family of stochastic models, which is able to represent drift. It is shown that, with these general assumptions, it is possible to identify some dynamic process models commonly encountered in manufacturing. After identification, our approach suggests to tune the controller to a near-optimal setting according to a well-known performance criterion. Copyright © 2001 John Wiley & Sons, Ltd. [source] Supervised classification and tunnel visionAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2005David J. Hand Abstract In recent decades many highly sophisticated methods have been developed for supervised classification. These developments involve complex models requiring complicated iterative parameter estimation schemes, and can achieve unprecedented performance in terms of misclassification rate. However, in focusing efforts on the single performance criterion of misclassification rate, researchers have abstracted the problem beyond the bounds of practical usefulness, to the extent that the supposed performance improvements are irrelevant in comparison with other factors influencing performance. Examples of such factors are given. An illustration is provided of a new method which, for the particular problem of credit scoring, improves a relevant measure of classification performance while maintaining interpretability. Copyright © 2005 John Wiley & Sons, Ltd. [source] Carotid artery revascularization in high surgical risk patients with the NexStent and the Filterwire EX/EZCATHETERIZATION AND CARDIOVASCULAR INTERVENTIONS, Issue 7 20081-Year results in the CABERNET trial Abstract Objective: The multicenter, single-arm CABERNET trial evaluated outcomes in high-surgical-risk patients with carotid artery stenosis treated with the NexStent® plus FilterWire EX®/EZÔ Emboli Protection System. Background: For patients at high surgical risk, carotid artery stenting (CAS) offers a less invasive alternative to carotid endarterectomy (CEA). Methods: The trial enrolled 454 high-surgical-risk patients with carotid stenosis by angiography ,50% for symptomatic patients and ,60% for asymptomatic patients. The comparator primary endpoint was the 1-year major adverse event (MAE, defined as any death, stroke, or myocardial infarction [MI]) rate. It was compared with a proportionally weighted objective performance criterion (OPC) of 12.1% representative of published CEA results in similar patients plus a prespecified noninferiority margin (delta) of 4%. A second primary endpoint was the composite rate of 30-day MAE plus late (31,365 days) ipsilateral stroke. Results: Symptoms of carotid stenosis were present in 24.2% of patients; 36.6% of patients were considered high-surgical-risk due to comorbid risk factors and 63.4% due to anatomic risk factors. The rate of 30-day MAE plus late ipsilateral stroke was 4.7% (20/438). The comparator primary endpoint of 1-year MAE was 11.6% (51/438) and was noninferior to the OPC of 12.1% (95% upper confidence interval of 14.5% versus OPC plus delta of 16.1%, P = 0.005). Late ipsilateral stroke was 0.7% and target vessel revascularization at 1 year was 2.4%. Conclusions: The CABERNET trial demonstrates that CAS with NexStent and FilterWire is noninferior to (equivalent or better than) traditional CEA at 1 year in high-surgical-risk patients based on historical controls. © 2008 Wiley-Liss, Inc. [source] | ||||||||||