Do not use this module, but use instead the more powerful uncertainties.py module.
Module for performing calculations with error propagation, such as (1 +- 0.1) * 2 = 2 +- 0.2. Mathematical operations (addition, etc.), operations defined in the math module (sin, atan,...) and logical operations (<, >, etc.) can be used.
Correlations between parts of an expression are correctly taken into account (for instance, the...
Most pH control processes are inherently high nonlinear and uncertainties with large time delay and therefore cannot be adequately controlled with a conventional PI control. In our term project, an approach to pH neutralization process control...
The problem of fitting a straight line to data with uncertainties in both coordinates is solved using a weighted total least-squares algorithm. The parameters are transformed from the usual slope/y-axis intersection pair to slope angle and...
The problem of fitting a straight line to data with uncertainties in both coordinates is solved using a weighted total least-squares algorithm. The parameters are transformed from the usual slope/y-axis intersection pair to slope angle and...
calculates surface area A and its standard uncertainty uA for any arbitrary polygon in a plane given by coordinates x and y and their respective standard uncertainties ux and uy. The inputs are assumed to be VECTORS, x, ux, y and uy all should...
The struct has two levels. The first level is the name of the constant. The second level has fields: "value", "uncert" and "unit". Example: phc = fundamentalPhysicalConstantsFromNIST(); ...
pbest=EASYFIT(x,y,varargin)
fits the data Y = f(X) to a model function Y = FUN(P,X). If FUN is not given as an input argument, POLYFIT is used as the model function. Bounds on the parameters P may be set. By default a...
It is desired for modern process systems to achieve optimal operation. However, operation at a pre-designed nominally optimal point may not necessarily be actually optimal due to realtime disturbances, measurement and control errors and...
fitChiSquare is a generalized chi-square fitting routine for any model function when data measurement errors are known; it returns the model parameters and their uncertainties at the delta chi-square = 1 boundary (68% confidence interval). It also...
The purpose of Input Shaping is to filter out big changes (typically steps) in the reference signal of a closed-loop system which excite all the modes of the plant causing relevant snap overshoots and oscillations in the response.
The...
Calculates slope and intercept for linear regression of data with errors in X and Y. The errors can be specified as varying point to point, as can the correlation of the errors in X and Y.
The uncertainty in the slope and intercept are...
Design of a robust digital controller with PPR toolbox
This script shows the basic steps for the "digital two degrees of freedom controller" (2DOF) design with the PPR toolbox.
The illustration of our methodology is...
Frink is a practical calculating tool and programming language designed to help us all to better understand the world around us, to help us get calculations right without getting bogged down in the mechanics, and to make a tool that's really...
easyfitGUI(varargin) fits real data Y = f(X) easyfitGUI open a figure with uimenus devoted to process the data. VARARGIN: one or several matrix [X, Y] having: first column = vector of the independant variable...
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