Hi;
Process modeling is the concise description of the total variation in one quantity, y, by partitioning it into
a deterministic component given by a mathematical function of one or more other quantities, x1, x2, ... , plus
a random component that follows a particular probability distribution.
For example, the total variation of the measured pressure of a fixed amount of a gas in a tank can be described by partitioning the variability into its deterministic part, which is a function of the temperature of the gas, plus some left-over random error. Charles' Law states that the pressure of a gas is proportional to its temperature under the conditions described here, and in this case most of the variation will be deterministic. However, due to measurement error in the pressure gauge, the relationship will not be purely deterministic. The random errors cannot be characterized individually, but will follow some probability distribution that will describe the relative frequencies of occurrence of different-sized errors.
Using the example above, the definition of process modeling can be graphically depicted like this:
The top left plot in the figure shows pressure data that vary deterministically with temperature except for a small amount of random error. The relationship between pressure and temperature is a straight line, but not a perfect straight line. The top row plots on the right-hand side of the equals sign show a partitioning of the data into a perfect straight line and the remaining "unexplained" random variation in the data (note the different vertical scales of these plots). The plots in the middle row of the figure show the deterministic structure in the data again and a histogram of the random variation. The histogram shows the relative frequencies of observing different-sized random errors. The bottom row of the figure shows how the relative frequencies of the random errors can be summarized by a (normal) probability distribution.
Process modelling helps to know the plant behavior. It has been reported that Model based controller design performs better on plant with closed-loop. Relay feedback technique is one of the most accepted modelling technique in process industry.
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