January 5, 2019 Compiled on January 30, 2024 at 11:29pm
This note shows how to solve using Mason’s rule method. Mason rule is used to obtain the
transfer function between two nodes in a signal graph, used in control systems, but can also
be used to solve a set of linear equations. This shows an example of how to use this method
to solve the following system Where The solution to above, which can easily be found using
Gaussian elimination is
The first step in Mason rule, is to decide on which are the variables that will be the nodes.
Clearly here the variables are . So we write the three equations, with each one having one of
those variables on the left side and everything to the right side. This gives the following three
equations
The above three equations are a rewrite of the original three equations in (1). It does not
matter which variable to move to the left from each equation, as long as we have one variable
moved to the left each time. Now we draw the signal graph from (2). Each node is a variable.
Arrows are drawn from the other variables (on the RHS) to the variable on the
LHS. The weight on the arrow is the coefficient next to each other variable. We
use the number as a node since it stands on its own. The result is the following
diagram
We now need to decide which is the input and which is the output. If we want to solve for
first, then we make the output and always make the numerical value as input, since it is
known. Hence we are looking for the transfer function . The first step in Mason
method is to find all forward paths from to . There are two in this case, they
are
Next we find all closed loops, there are three
Next we find associated with each . These are found by removing path from the graph and
recalculated the Mason for what is left. In this case we see that and . Now we are ready to
find Now that we found one variable, we do the same for the next variable. Let us pick as
the output now, so we are looking for . In this case, there are four forward paths from to
The loops remain the same as before, since the loops do not change as the graph remains the
same. We now just need to recalculate the associated with each . From the graph we see
that and Hence Now we will find the final unknown, which is . Now is the output. In this
case, there are three forward paths from to
Now we find the associated with each . From the graph we see that Hence Therefore the
three variables are