In mathematical analysis, the final value theorem (FVT) is one of several similar theorems used to relate frequency domain expressions to the time domain behavior as time approaches infinity. A final value theorem allows the time domain behavior to be directly calculated by taking a limit of a frequency domain expression, as opposed to converting to a time domain expression and taking its limit.
Contents
Mathematically, if
has a finite limit, then
where
Likewise, in discrete time
where
Proof
By integrating from the definition of Laplace transform of a derivative we have:
If the infinite integral on LHS exists, then the limit of integral can be written as integral of limit, therefore:
By equating RHSs of previous equations and canceling f(0) on both sides:
Example where FVT holds
For example, for a system described by transfer function
and so the impulse response converges to
That is, the system returns to zero after being disturbed by a short impulse. However, the Laplace transform of the unit step response is
and so the step response converges to
and so a zero-state system will follow an exponential rise to a final value of 3.
Example where FVT does not hold
However, for a system described by the transfer function
the final value theorem appears to predict the final value of the impulse response to be 0 and the final value of the step response to be 1. However, neither time-domain limit exists, and so the final value theorem predictions are not valid. In fact, both the impulse response and step response oscillate, and (in this special case) the final value theorem describes the average values around which the responses oscillate.
There are two checks performed in Control theory which confirm valid results for the Final Value Theorem:
- All nonzero roots of the denominator of
H ( s ) must have negative real parts. -
H ( s ) must not have more than one pole at the origin.
Rule 1 was not satisfied in this example, in that the roots of the denominator are