Experimental evaluation of a multivariable adaptive nonlinear predictive controller

A new multivariable adaptive nonlinear predictive controller is designed using a general nonlinear input-output model and variable transformations. The controller is similar in form to typical linear predictive controllers can be tuned analogously or by specifying a single parameters for each controlled variable. In addition, the design procedure is computationally efficient. The new controller is compared to a multi-loop proportional-integral (PI) controller with one-way static decoupling and to an adaptive linear predictive controller through tests on a simulated nonlinear distillation column. The new controller performed well in an experimental application to a multicomponent distillation column.     

Determination of model order for NARX models directly from input-output data

Nonlinear auto-regressive models with exogenous inputs (NARX models) have proved to be versatile and useful empirical models for industrial processes. There are a wide variety of identification methods and model structures from which to choose; in all methods, however, key parameters are the model orders, which are the number of past outputs and inputs used in the model. In this paper the methods of Lipschitz numbers and false nearest neighbors are evaluated as a means of estimating the model orders of dynamic, discrete-time NARX models. No specific model structure is assumed and the model orders are estimated directly from input-output data using only geometric concerns and the continuity property. The two methods are applied to several dynamic systems, including realistic process simulations and experimental data from the UCSB pH neutralization process, and the consistency and accuracy of these methods are examined. The usefulness of these methods of model order determination for radial basis function network (RBFN) identification is examined.     

Identification of the Tennessee Eastman challenge process with subspace methods

The Tennessee Eastman challenge process is a realistic simulation of a chemical process that has been widely used in process control studies. In this case study, several identification methods are examined and used to develop MIMO models that contain seven inputs and ten outputs. ARX and finite impulse response models are identified using reduced-rank regression techniques (PLS and CCR) and state-space models identified with prediction error methods and subspace algorithms. For a variety of reasons, the only successful models are the state-space models produced by two popular subspace algorithms, N4SID and canonical variate analysis (CVA). The CVA model is the most accurate. Important issues for identifying the Tennessee Eastman challenge process and comparisons between the subspace algorithms are also discussed.     

The effect of mother–child separation on the behavior of children experiencing a diagnostic medical procedure.

54 4–6 and 7–10 yr olds were observed having a venal puncture blood sample drawn in a clinical laboratory with or without their mothers being present. Younger Ss exhibited significantly more crying before and during the blood test, more aggression, and more resistance to the procedure than did older Ss, regardless of experimental condition. The mother-present condition only affected crying before the initiation of the blood test. Ss in both age groups displayed significantly more crying when their mothers were present than when their mother remained in the waiting room. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Length of stay, neuropsychological performance, and aftercare: Influences on alcohol-treatment outcome.

Hypothesized that 245 alcohol-abusing male veterans, grouped according to levels of neuropsychological functioning, would have differential outcome following random assignment to 2- or 7-wk hospitalization in a milieu-oriented treatment program. Over the 9 mo of posthospitalization follow-up, there was significant improvement for the sample as a whole. However, outcome following 2- and 7-wk programs did not differ significantly. Neuropsychological performance was significantly but modestly related to some outcome criteria (e.g., abstinence rates and employment status), but no consistent interaction with length of stay was found. The most salient finding was the strong relationship of aftercare involvement (which was analyzed as a covariate) to most outcome criteria. Ss who attended weekly aftercare groups for 9 mo following hospitalization were 3 times more likely to remain abstinent than Ss who dropped out of aftercare (70.2 vs 23.4% abstinence, respectively). Implications for individualizing alcohol treatment and conducting future research on patient–treatment matching are discussed. (59 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Psychological aspects of severe burn injuries in children.

Discusses 4 phases of the traumatic process associated with severe burn injuries in children. Predisposing factors (i.e., emotional disturbances) in the preinjury phase are discussed. The acute phase centers on treatment directed toward physiological stabilization. The intermediate phase, in which skin grafts and other painful medical procedures are performed, is characterized by dependency on adults and regression, behavior problems, and such emotional reactions as blaming the parents. Strategies for preparing children for and helping them cope with pain are discussed. The rehabilitative phase often involves difficulties in social readjustment. Strategies for dealing with each phase are presented, most of which focus on prevention efforts. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Determination of platinum in blood by adsorptive voltammetry

This work describes a sensitive method for the determination of platinum in blood, which can be used for determining the natural levels of platinum in human blood, for monitoring patients treated with platinum cytotoxic drugs, and for monitoring occupational exposure to these drugs and other platinum compounds. The method involves dry ashing of blood samples in a muffle furnace and determination of platinum by adsorptive voltammetric (AV) measurement of the catalytic reduction of protons by the platinum-formazone complex. The detection limit for a 100-microL sample of blood is 0.017 micrograms/L, with a recovery of 94% and a relative standard deviation of 7% at a platinum level of 1 microgram/L. By using this method, the natural levels of platinum in human blood were found to be in the range 0.1-2.8 micrograms/L (median = 0.6 micrograms/L). These results were verified by inductively coupled plasma mass spectrometry (ICP-MS) with blood prepared by wet ashing and using gold as an internal standard.     

A New Metric for Grey-Scale Image Comparison

Error measures can be used to numerically assess the differences between two images. Much work has been done on binary error measures, but little on objective metrics for grey-scale images. In our discussion here we introduce a new grey-scale measure, ^g, aiming to improve upon the most common grey-scale error measure, the root-mean-square error. Our new measure is an extension of the authors' recently developed binary error measure, ^b, not only in structure, but also having both a theoretical and intuitive basis. We consider the similarities between ^b and ^g when tested in practice on binary images, and present results comparing ^g to the root-mean-squared error and the Sobolev norm for various binary and grey-scale images. There are no previous examples where the last of these measures, the Sobolev norm, has been implemented for this purpose.     

Supporting browsing-specific information needs: Introducing the Citation-Sensitive In-Browser Summariser

Practitioners and researchers need to stay up-to-date with the latest advances in their fields, but the continual growth in the amount of literature available makes this task increasingly difficult. In this article, we describe the Citation-Sensitive In-Browser Summariser (CSIBS), a new research tool to help manage the literature browsing task. The design of CSIBS was based on a user requirements analysis which identified the information needs that biomedical researchers commonly encounter when browsing through academic literature. CSIBS supports researchers in their browsing tasks by presenting both a generic and a tailored preview about a citation at the point at which they encounter it. This information is aimed at helping the reader determine whether or not to invest the time in exploring the cited article further, thus alleviating information overload. Feedback from biomedical researchers indicates that CSIBS facilitates this relevance judgement task, and that the interface and previews are informative and easy to use.     

Optimal selection of soft sensor inputs for batch distillation columns using principal component analysis

In this paper, a novel methodology based on principal component analysis (PCA) is proposed to select the most suitable secondary process variables to be used as soft sensor inputs. In the proposed approach, a matrix is defined that measures the instantaneous sensitivity of each secondary variable to the primary variables to be estimated. The most sensitive secondary variables are then extracted from this matrix by exploiting the properties of PCA, and they are used as input variables for the development of a regression model suitable for on-line implementation.This method has been evaluated by developing a soft sensor that uses temperature measurements and a process regression model to estimate on-line the product compositions for a simulated batch distillation process. The identification of the optimal soft sensor inputs for this case study has been discussed with respect to the definition of the sensitivity matrix, the data sampling interval, the presence of measurement noise, and the size of the input set. The simulation results demonstrate that the proposed approach can effectively identify the size and configuration of the input set that leads to the optimal estimation performance of the soft sensor.