Step Changes In Parameters Research Articles

Design and Implementation of a New Algorithm for Fast Diagnosis of Step Changes in Parameters of Continuous Systems

In this paper special adaptation of modulating functions method MFM for fast detection of step changes in parameters of continuous and linear systems is presented. The modulating functions method is well known for identification of continuous, linear, time-invariant system CLTIS. The characteristic feature of MF method in its application to the problem of identification of step changes in parameters is the existence of fixed time delay in the reconstruction of the new value of parameters after their failure. The aim of this paper is presentation of the substantial modification of MFM which enables optimal identification of parameter faults with minimization of time delay.

Refractive phenomena in the shock wave dispersion with variable gradients

In this article the refraction effects in the weak shock wave (SW) dispersion on an interface with a temperature variation between two mediums are described. In the case of a finite-gradient boundary, the effect of the SW dispersion is remarkably stronger than in the case of a step change in parameters. In the former case the vertical component of velocity for the transmitted SW (the refraction effect) must be taken into account. Results of comparative calculations based on the two-dimensional model corrected for the refraction effect show significant differences in the shapes of the dispersed SW fronts.

FREQUENCY DOMAIN CLOSED-LOOP ANALYSIS AND SLIDING MODE CONTROL OF A NONMINIMUM PHASE BUCK–BOOST CONVERTER

In this paper, a robust closed-loop cascaded controller is designed and analysed for an inverting buck-boost converter. The fast inner current loop uses sliding mode control (SMC). The slow outer voltage loop uses the proportional-integral (PI) control. Analysis of stability and robustness, proof of nonminimum phase structure, and proper selection of PI gains are based on the closed-loop transfer function. The controller design is facilitated by the system frequency responses. The output voltage transients caused by step changes of the input voltage and load resistance are predictable. The operating range of the reference voltage is discussed. The simulation results show that the reference output voltage is well tracked under modelling uncertainties, disturbances or step changes of parameters, confirming the validity of the proposed method.

Statistical Process Control for Shifts in Mean or Variance Using a Changepoint Formulation

Statistical process control (SPC) involves ongoing checks to ensure that neither the mean nor the variability of the process readings has changed. Conventionally, this is done by pairs of charts—Shewhart X and S (or R) charts, cumulative sum charts for mean and for variance, or exponentially weighted moving average charts for mean and variance. The traditional methods of calculating the statistical properties of control charts are based on the assumption that the in-control true mean and variance were known exactly, and use these assumed true values to set center lines, control limits, and decision intervals. The reality, however, is that true parameter values are seldom if ever known exactly; rather, they are commonly estimated from a phase I sample. The random errors in the estimates lead to uncertain run length distribution of the resulting charts. An attractive alternative to the traditional charting methods is a single chart using the unknown-parameter likelihood ratio test for a change in mean and/or variance in normally distributed data. This formulation gives a single diagnostic to detect a shift in mean, in variance, or in both, rather than two separate diagnostics. Using the unknown parameter formulation recognizes the reality that at best one has reasonable estimates of parameters and not their exact values. This description implies an immediate benefit of the formulation, that the run behavior is controlled despite the lack of a large phase I sample. We demonstrate another benefit, that the changepoint formulation is competitive with the best of traditional formulations for detecting step changes in parameters.

Effects of cardiopulmonary bypass on sufentanil pharmacokinetics in patients undergoing coronary artery bypass surgery.

Complete pharmacokinetic modeling, including assessment of the effect of cardiopulmonary bypass (CPB) on sufentanil disposition, has not been reported. The aims of this investigation were to define a model that accurately predicted sufentanil concentrations during and after cardiac surgery and to determine if CPB had a clinically significant impact on sufentanil pharmacokinetics. Population pharmacokinetic modeling was applied to data from 21 patients undergoing coronary artery bypass grafting. The predictive ability of models was assessed by calculating bias, accuracy, and measured:predicted concentration ratios versus time. A simple three-compartment model, without covariates, was initially compared with models having weight or gender as covariates and was subsequently used as the foundation for multiple CPB-adjusted models (allowing step-changes of parameters at the start or end of CPB). The primary criterion for choosing more complex models was a significant improvement in log-likelihood; secondary criteria were significant improvement in bias or accuracy. Neither covariate (weight or gender) models improved bias or accuracy compared with the simple three-compartment model. A final CPB-adjusted model with V2 and Cl3 changing at the start of CPB and V1, Cl2, and Cl3 changing at the end of CPB had significantly greater log-likelihood values when compared with the simple three-compartment model and with less elaborate CPB-adjusted models. However, bias and accuracy for this final model were not significantly different from the simple three-compartment model. When sufentanil is infused at a constant rate, with initiation of CPB, a pharmacokinetic model adjusted for CPB predicts that the sufentanil concentration will decrease approximately 17% and that it will begin to return to the prebypass concentration 12 min after initiation of CPB. At the end of CPB, this model also predicts a brief spike of the sufentanil concentration. These predictions reflect changes in the measured sufentanil concentrations. However, compared with a simple, three-compartment model, incorporating step-changes of pharmacokinetic parameters at the start or end of cardiopulmonary bypass (or both) did not significantly improve overall perioperative prediction of measured sufentanil concentrations. This suggests that CPB has clinically insignificant effects on sufentanil kinetics in adults.

Mechanisms of length history-dependent tension in an ionic model of the cardiac myocyte.

The ionic model of the ventricular myocyte developed by Luo and Rudy (Circ. Res. 74: 1071-1096, 1994) was used to investigate potential mechanisms of the slow changes in stress (SCS) that follow step changes in muscle length. A step change in myofilament sensitivity alone caused an immediate increase in active tension, but no SCS. The effects of additional step changes in the parameters of sarcolemmal ion fluxes were examined for each ion flux in the model. Changes in the coefficients of Ca2+ or K+ channels did not produce SCS. SCS was produced by step changes in parameters of the Na(+)-K+ pump or the Na+ leak current. This simulated mechanism was mediated through a slow increase in intracellular Na+ concentration and a resulting increase in systolic Ca2+ entry through the Na+/Ca2+ exchanger. The model reproduced the effects of several experimental interventions such as sarcoplasmic reticulum Ca2+ depletion, "diastolic" length changes, and changes in extracellular Ca2+. Thus SCS in cardiac muscle may be caused by length-induced changes in sarcolemmal Na+ fluxes.

Adaptive Control of a Flexible Structure

The design of a high-performance adaptive controller is discussed for an experimental lightly-damped flexible structure. The plant, the Stanford Four-Disk System, sustains large step changes in parameters as payload mass is added. New methods that make use of limited a priori knowledge of the plant are shown not only to greatly improve the quality of the identification in the presence of measurement noise and other disturbances, but greatly reduce the number of parameters that need be identified. The methods make use of known plant dynamics, frequency bands where unknown, modeled dynamics may exist and the natural damping of such dynamics. A method of dynamic pole-placement that ensures good step response, a high degree of active damping of modeled modes, modest amounts of control effort and low computational intensity is presented. A controller structure that ensures bumpless transfer between leapfrogging adaptive controllers and a standby robust controller is discussed. The performance of the adaptive non-colocated compensator, a robust colocated compensator and a robust non-colocated compensator are compared. The experimental adaptive controller dramatically outperforms the robust compensators within several seconds after a major change in plant parameters.