Sentence examples for model parameter variations from inspiring English sources

This paper is the second part of this work and is devoted to the study of the observer and residual sensitivity towards model parameter variations and noises.

In order to simulate the electrophysiological experiments more realistically, uncertainties including model parameter variations, noises with arbitrary intensities and changes of inner states are introduced in the model.

The present paper investigates the impact of Mann turbulence model parameter variations on the design loads envelope for 5 MW and 10 MW reference wind turbines.

Another interesting aspect of Figure 2(b) is that away from the quantum critical point, the composite parameter is mostly composed of model parameter variations near the spins whose correlation is being evaluated.

A method is developed that screens process flowsheet and control system configurations, defined in terms of selected controlled and manipulated variables that exhibit poor steady-state behavior under the presence of multiple simultaneous disturbances and model parameter variations.

Then, the sensitivity of the inductor characterization to the model parameter variations is obtained through a simulation-based approach, where the Richardson extrapolation technique is used for the calculation of the partial derivatives.

Thus, stability robustness in terms of both model parameter variation and controller parameter adjustments can be systematically explored.

Multidimensional covariate effects are incorporated at each stage using penalised (tensor products of) B-splines to give smooth model parameter variation as a function of multiple covariates.

In this paper, the modelling of an energy generation system based on polymer electrolyte membrane fuel cell (PEMFC) system through a parameter varying approach (LPV model), that takes in to account model parameter variation with the operating point, is presented.

The effect of model parameter variation on control performance is discussed, and its impact on the controller implementation is investigated with a view to determining the most suitable parameters for online adaptation.

The on-line model is used for mill condition monitoring in two ways: (i) to compare the predicted and measured mill output pressure and temperatures and to raise alarms if there are big discrepancies; and (ii) to monitor the mill model parameter variation patterns which detect the potential faults and mill malfunctions.