Dynamic Nonlinear Regression Research Articles

Characterizing the biofilm stoichiometry and kinetics on the media in situ based on pulse-flow respirometer coupling with a new breathing reactor

Biofilm based systems and the hybrid between activated sludge and biofilms have been popularly applied for wastewater treatment. Unlike the suspended biomass, the biofilm concentration and kinetics on the media cannot be easily measured. In this study, a novel and easy-to-use approach has been developed based on pulse-flow respirometer to characterize the biofilm stoichiometry and kinetics in situ. With the new designed breathing reactor, the mutual interference between the magnetic stirring and biofilm media that happened in the conventional breathing reactor was solved. Moreover, Microsoft Excel based programs had been developed to fit the oxygen uptake rate curves with dynamic nonlinear regression. With this new approach, the yield coefficient, maximum oxidation capacity, and half-saturation constant of substrate for the heterotrophic biofilms in a fix bed reactor were determined to be 0.46 g-VSS/g-COD, 67.0 mg-COD/(h·L-media), and 4.4 mg-COD/L, respectively. Those parameters for biofilm ammonia oxidizers from a moving bed biofilm reactor were determined to be 0.17 g-VSS/g-N, 18.6 mg-N/(h·L-media), and 1.2 mg-N/L, respectively, and they were 0.11 g-VSS/g-N, 20.9 mg-N/(h·L-media), and 0.98 mg-N/L for nitrite oxidizers in the same biofilms. This study also found that the maximum specific substrate utilization rate for detached biofilms increased by 3.2 times, indicating that maintaining biofilm integrity was very important in the kinetic tests. Using this approach, the biofilm kinetics on the media can be regularly measured for treatment optimization.

Ash fouling monitoring and soot-blow optimization for reheater in thermal power plant

The paper investigates a comprehensive approach for ash fouling monitoring and an optimized soot-blow mechanism for a thermal power plant reheater. A dynamic nonlinear regression model is designed to monitor the Cleanliness Factor (CF) of reheater and thereby an optimized soot-blow strategy is proposed to determine the critical CF and the duration of soot-blow cycle. The result in this case-study shows that steam consumed per soot-blow cycle is reduced and also the amount of fuel used per day is saved by adopting the proposed soot-blow strategy. The proposed method can be implemented as guidance for soot-blow operation in thermal power plants without any need for additional hardware and with a minimal computation.

Estimation and Inference under Weak Identification and Persistence in Dynamic Nonlinear Regression

The reaction coefficients in the forecast-based monetary policy reaction function are only weakly identified when the smoothing coefficient for the nominal interest rate is close to unity. This situation also causes the nominal interest rate to be highly persistent. Inference based on the standard strong identification assumption and recently developed identification robust procedures based on stationarity fail in this setting, and we propose modifications. In particular, based on nonlinear least squares (NLS) estimation, we develop valid confidence sets for reaction coefficients that are robust to a wide range of the smoothing coefficient, including close and distant neighborhoods of unity. Allowing for both potential weak identification and a nearly unit root constitutes the novelty of the suggested procedure. Our empirical application using recently available real-time data suggests that, whether the estimates are accurate enough to rule out the possibility of indeterminacy in US monetary policy depends on forecast horizons of expected inflations and output gaps used in the model.

Sliding-Mode Tracking Control With DNLRX Model-Based Friction Compensation for the Precision Stage

This paper concerns the development of a sliding-mode tracking controller with friction compensation for a precision positioning stage with cross-roller guides. Experiments including prerolling and rolling friction regimes are conducted, and then a two-stage parameter estimation algorithm is used to identify the parameters of a friction dynamic model (Dynamic NonLinear Regression with direct application of eXcitation, DNLRX, model). This model allows the estimation of the friction force in combination with the system dynamics against displacement, and can be used as a feed-forward controller to compensate for the friction effect. To compensate for model error and uncertain disturbances, an integral sliding-mode controller with a disturbance estimation scheme is designed and combined with the DNLRX feed-forward controller to control the motion of a precision stage. Experimental results show that with the proposed controller, tracking performance can be improved.

The Link Between Health Care Systems and Financing: Evaluation of Payment Systems in Selected OECD Countries

Background: Financial incentives and institutions play a key role in determining health care expenditures. The health care sector in Europe is mostly publicly funded and financed in contrast to other OECD-countries. The financing is through taxes and service provision by public hospitals and health centers in the Nordic countries. In contrast the corresponding public shares are close to or below 50 percent in the Netherlands, in Switzerland especially in the USA. Aims: The following questions are to be investigated in this article. Firstly how does the budgeting model influence health care spending. Secondly how does the public share of health care spending correlate with total spending. And thirdly how do other factors, such as exogenous technological change, relative prices of health care etc. affect health spending. Methods: The research panel data is drawn out from OECD Health Data 2007. It includes 10 industrialized countries with different health care systems from 1971 to 2005. A dynamic nonlinear regression model is estimated for the data. Results: The main results of the study are that in the sample the fee-for-service system in primary care is 22 percent higher in HCE costs and on the contrary the global budgeting of hospitals is 34 percent lower in costs. Conclusions: The key in provision of specialized health care services is that the political and economic incentives of budget setters are passed through to service providers more closely when they act in the same organizational framework. Publicly financed and produced systems do well in comparison to insurance based and privately funded and organized health care schemes.

Friction Identification Based Upon the LuGre and Maxwell Slip Models

The problem of friction identification within the presliding and sliding regimes is addressed and three identification methods, designated as the LuGre (LG) method, the nonlinear regression (NLR) method, and dynamic nonlinear regression with direct application of the excitation (DNLRX) method, are postulated. The first employs the LG model structure, the second the basic Maxwell slip model structure, and the third an extended version of it. The Maxwell Slip model structure accounts for the presliding hysteresis with nonlocal memory, but is confined to providing constant sliding friction. This limitation is circumvented by the postulated extended version. In all methods identification is based upon signals obtained from a single experiment. The methods are successfully assessed via Monte Carlo experiments, as well as via a laboratory setup. The DNLRX is shown to achieve the best overall performance, followed by the NLR and LG methods. A simple DNLRX-based feedforward friction compensation scheme is also postulated and assessed. The results indicate that it is capable of yielding effective friction compensation.

Simultaneous Determination of Hydrolysis and Mutarotation Rates during the Enzymatic Hydrolysis of Lactose

An experiment is described in which a custom-made glucose electrode is used to directly monitor the enzymatic hydrolysis of lactose to glucose. The transient profile of beta- d-glucose can be used to simultaneously determine the rate constants for mutarotation and for enzymatic hydrolysis by applying a dynamic nonlinear regression routine. Due to differences in the mutarotation rate constants between lactose and glucose, the beta- d-glucose concentration "overshoots" equilibrium under certain conditions, which can be modeled mathematically. This overshoot can be observed reliably and used to quantify the differences in mutarotational equilibria between glucose and lactose. These observations may be important for the analysis of dairy products and commercial lactase preparations and illustrate an unusual kinetic phenomenon caused by intramolecular forces. This approach may also be important for the accurate determination of a variety of oligosaccharides such as glycogen, which tend to be composed primarily of one stereoisomer.

Generalised NARX shunting neural network modelling of friction

This paper describes the modelling of dry friction using a NARX (Nonlinear AutoRegressive with eXogeneous inputs) type shunting neural network model. An ensemble model is then constructed by combining the shunting neural network model with the physics based DNLR (dynamic nonlinear regression) Maxwell slip model.

FRICTION IDENTIFICATION BASED UPON THE LUGRE AND MAXWELL SLIP MODELS

Three friction identification methods, designated as the LuGre (LG) method, the Non-Linear Regression (NLR) method, and the Dynamic Non-Linear Regression with direct application of the eXcitation (DNLRX) method, are postulated. The first employs the LuGre model structure, the second the basic Maxwell Slip model structure, and the third an extended version of it. The Maxwell Slip model structure accounts for the presliding hysteresis with nonlocal memory, but is confined to providing constant sliding friction. This limitation is circumvented by the extended version postulated, where additional dynamics are introduced. In all methods identification is based upon signals obtained from a single experiment, thus circumventing the need for multiple experiments. The methods are assessed via laboratory signals, and the DNLRX is shown to achieve the best overall performance, followed by the NLR and, finally, the LG method.

A dynamic nonlinear regression method for the determination of thediscrete relaxation spectrum

The relaxation spectrum is animportant tool for studying the behaviour of viscoelasticmaterials. The most popular procedure is to use data froma small-amplitude oscillatory shear experiment to determinethe parameters in a multi-mode Maxwell model. However,the discrete relaxation times appear nonlinearly inthe mathematical model for the relaxation modulus.The indirect calculation of the relaxationtimes is an ill-posed problem and its numerical solution isfraught with difficulties. The ill-posedness of the linearregression approach, in which the relaxation times arespecified a priori and the minimization is performed withrespect to the elastic moduli, is well documented.A nonlinear regression technique is described in this paperin which the minimization is performedwith respect to both the discrete relaxationtimes and the elastic moduli. In this technique the number ofdiscrete modes is increased dynamically andthe procedure is terminated whenthe calculated values of the model parameters aredominated by a measure of their expected values.The sequence of nonlinear least-squares problems,solved using the Marquardt-Levenberg procedure,is shown to be robust and efficient. Numericalcalculations on model and experimental data are presentedand discussed.