Final value theorem

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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.[1][2][3][4] Mathematically, if f(t) in continuous time has (unilateral) Laplace transform F(s), then a final value theorem establishes conditions under which

limtf(t)=lims0sF(s)

Likewise, if f[k] in discrete time has (unilateral) Z-transform F(z), then a final value theorem establishes conditions under which

limkf[k]=limz1(z1)F(z)

An Abelian final value theorem makes assumptions about the time-domain behavior of f(t) (or f[k]) to calculate lims0sF(s). Conversely, a Tauberian final value theorem makes assumptions about the frequency-domain behaviour of F(s) to calculate limtf(t) (or limkf[k]) (see Abelian and Tauberian theorems for integral transforms).

Final value theorems for the Laplace transform

Deducing limt → ∞ f(t)

In the following statements, the notation 's0' means that s approaches 0, whereas 's0' means that s approaches 0 through the positive numbers.

Standard Final Value Theorem

Suppose that every pole of F(s) is either in the open left half plane or at the origin, and that F(s) has at most a single pole at the origin. Then sF(s)L as s0, and limtf(t)=L.[5]

Final Value Theorem using Laplace transform of the derivative

Suppose that f(t) and f(t) both have Laplace transforms that exist for all s>0. If limtf(t) exists and lims0sF(s) exists then limtf(t)=lims0sF(s).[3]:Theorem 2.36[4]:20[6]

Remark

Both limits must exist for the theorem to hold. For example, if f(t)=sin(t) then limtf(t) does not exist, but lims0sF(s)=lims0ss2+1=0.[3]:Example 2.37[4]:20

Improved Tauberian converse Final Value Theorem

Suppose that f:(0,) is bounded and differentiable, and that tf(t) is also bounded on (0,). If sF(s)L as s0 then limtf(t)=L.[7]

Extended Final Value Theorem

Suppose that every pole of F(s) is either in the open left half-plane or at the origin. Then one of the following occurs:

  1. sF(s)L as s0, and limtf(t)=L.
  2. sF(s)+ as s0, and f(t)+ as t.
  3. sF(s) as s0, and f(t) as t.

In particular, if s=0 is a multiple pole of F(s) then case 2 or 3 applies (f(t)+ or f(t)).[5]

Generalized Final Value Theorem

Suppose that f(t) is Laplace transformable. Let λ>1. If limtf(t)tλ exists and lims0sλ+1F(s) exists then

limtf(t)tλ=1Γ(λ+1)lims0sλ+1F(s)

where Γ(x) denotes the Gamma function.[5]

Applications

Final value theorems for obtaining limtf(t) have applications in establishing the long-term stability of a system.

Deducing lims → 0 sF(s)

Abelian Final Value Theorem

Suppose that f:(0,) is bounded and measurable and limtf(t)=α. Then F(s) exists for all s>0 and lims0+sF(s)=α.[7]

Elementary proof[7]

Suppose for convenience that |f(t)|1 on (0,), and let α=limtf(t). Let ϵ>0, and choose A so that |f(t)α|<ϵ for all t>A. Since s0estdt=1, for every s>0 we have

sF(s)α=s0(f(t)α)estdt;

hence

|sF(s)α|s0A|f(t)α|estdt+sA|f(t)α|estdt2s0Aestdt+ϵsAestdt=I+II.

Now for every s>0 we have

II<ϵs0estdt=ϵ.

On the other hand, since A< is fixed it is clear that lims0I=0, and so |sF(s)α|<ϵ if s>0 is small enough.

Final Value Theorem using Laplace transform of the derivative

Suppose that all of the following conditions are satisfied:

  1. f:(0,) is continuously differentiable and both f and f have a Laplace transform
  2. f is absolutely integrable - that is, 0|f(τ)|dτ is finite
  3. limtf(t) exists and is finite

Then

lims0+sF(s)=limtf(t).[8]

Remark

The proof uses the dominated convergence theorem.[8]

Final Value Theorem for the mean of a function

Let f:(0,) be a continuous and bounded function such that such that the following limit exists

limT1T0Tf(t)dt=α

Then lims0,s>0sF(s)=α.[9]

Final Value Theorem for asymptotic sums of periodic functions

Suppose that f:[0,) is continuous and absolutely integrable in [0,). Suppose further that f is asymptotically equal to a finite sum of periodic functions fas, that is

|f(t)fas(t)|<ϕ(t)

where ϕ(t) is absolutely integrable in [0,) and vanishes at infinity. Then

lims0sF(s)=limt1t0tf(x)dx.[10]

Final Value Theorem for a function that diverges to infinity

Let f(t):[0,) and F(s) be the Laplace transform of f(t). Suppose that f(t) satisfies all of the following conditions:

  1. f(t) is infinitely differentiable at zero
  2. f(k)(t) has a Laplace transform for all non-negative integers k
  3. f(t) diverges to infinity as t

Then sF(s) diverges to infinity as s0+.[11]

Final Value Theorem for improperly integrable functions (Abel's theorem for integrals)

Let h:[0,) be measurable and such that the (possibly improper) integral f(x):=0xh(t)dt converges for x. Then

0h(t)dt:=limxf(x)=lims00esth(t)dt.

This is a version of Abel's theorem.

To see this, notice that f(t)=h(t) and apply the final value theorem to f after an integration by parts: For s>0,

s0estf(t)dt=[estf(t)]t=o+0estf(t)dt=0esth(t)dt.

By the final value theorem, the left-hand side converges to limxf(x) for s0.

To establish the convergence of the improper integral limxf(x) in practice, Dirichlet's test for improper integrals is often helpful. An example is the Dirichlet integral.

Applications

Final value theorems for obtaining lims0sF(s) have applications in probability and statistics to calculate the moments of a random variable. Let R(x) be cumulative distribution function of a continuous random variable X and let ρ(s) be the Laplace–Stieltjes transform of R(x). Then the n-th moment of X can be calculated as

E[Xn]=(1)ndnρ(s)dsn|s=0

The strategy is to write

dnρ(s)dsn=(G1(s),G2(s),,Gk(s),)

where () is continuous and for each k, Gk(s)=sFk(s) for a function Fk(s). For each k, put fk(t) as the inverse Laplace transform of Fk(s), obtain limtfk(t), and apply a final value theorem to deduce lims0Gk(s)=lims0sFk(s)=limtfk(t). Then

dnρ(s)dsn|s=0=(lims0G1(s),lims0G2(s),,lims0Gk(s),)

and hence E[Xn] is obtained.

Examples

Example where FVT holds

For example, for a system described by transfer function

H(s)=6s+2,

the impulse response converges to

limth(t)=lims06ss+2=0.

That is, the system returns to zero after being disturbed by a short impulse. However, the Laplace transform of the unit step response is

G(s)=1s6s+2

and so the step response converges to

limtg(t)=lims0ss6s+2=62=3

So a zero-state system will follow an exponential rise to a final value of 3.

Example where FVT does not hold

For a system described by the transfer function

H(s)=9s2+9,

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:

  1. All non-zero roots of the denominator of H(s) must have negative real parts.
  2. 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 0+j3 and 0j3.

Final value theorems for the Z transform

Deducing limk → ∞ f[k]

Final Value Theorem

If limkf[k] exists and limz1(z1)F(z) exists then limkf[k]=limz1(z1)F(z).[4]:101

Final value of linear systems

Continuous-time LTI systems

Final value of the system

𝐱˙(t)=𝐀𝐱(t)+𝐁𝐮(t)
𝐲(t)=𝐂𝐱(t)

in response to a step input 𝐮(t) with amplitude R is:

limt𝐲(t)=𝐂𝐀1𝐁R

Sampled-data systems

The sampled-data system of the above continuous-time LTI system at the aperiodic sampling times ti,i=1,2,... is the discrete-time system

𝐱(ti+1)=Φ(hi)𝐱(ti)+Γ(hi)𝐮(ti)
𝐲(ti)=𝐂𝐱(ti)

where hi=ti+1ti and

Φ(hi)=e𝐀hi, Γ(hi)=0hie𝐀sds

The final value of this system in response to a step input 𝐮(t) with amplitude R is the same as the final value of its original continuous-time system. [12]

See also

Notes

  1. Wang, Ruye (2010-02-17). "Initial and Final Value Theorems". http://fourier.eng.hmc.edu/e102/lectures/Laplace_Transform/node17.html. Retrieved 2011-10-21. 
  2. Alan V. Oppenheim; Alan S. Willsky; S. Hamid Nawab (1997). Signals & Systems. New Jersey, USA: Prentice Hall. ISBN 0-13-814757-4. 
  3. 3.0 3.1 3.2 Schiff, Joel L. (1999). The Laplace Transform: Theory and Applications. New York: Springer. ISBN 978-1-4757-7262-3. 
  4. 4.0 4.1 4.2 4.3 Graf, Urs (2004). Applied Laplace Transforms and z-Transforms for Scientists and Engineers. Basel: Birkhäuser Verlag. ISBN 3-7643-2427-9. 
  5. 5.0 5.1 5.2 Chen, Jie; Lundberg, Kent H.; Davison, Daniel E.; Bernstein, Dennis S. (June 2007). "The Final Value Theorem Revisited - Infinite Limits and Irrational Function". IEEE Control Systems Magazine 27 (3): 97-99. doi:10.1109/MCS.2007.365008. 
  6. "Final Value Theorem of Laplace Transform". https://proofwiki.org/wiki/Final_Value_Theorem_of_Laplace_Transform. Retrieved 12 April 2020. 
  7. 7.0 7.1 7.2 Ullrich, David C. (2018-05-26). "The tauberian final value Theorem". https://math.stackexchange.com/q/2795640. 
  8. 8.0 8.1 Sopasakis, Pantelis (2019-05-18). "A proof for the Final Value theorem using Dominated convergence theorem". https://math.stackexchange.com/q/3218593. 
  9. Murthy, Kavi Rama (2019-05-07). "Alternative version of the Final Value theorem for Laplace Transform". https://math.stackexchange.com/questions/3216837/alternative-version-of-the-final-value-theorem-for-laplace-transform. 
  10. Gluskin, Emanuel (1 November 2003). "Let us teach this generalization of the final-value theorem". European Journal of Physics 24 (6): 591–597. doi:10.1088/0143-0807/24/6/005. 
  11. Hew, Patrick (2020-04-22). "Final Value Theorem for function that diverges to infinity?". https://math.stackexchange.com/q/3637843. 
  12. Mohajeri, Kamran; Madadi, Ali; Tavassoli, Babak (2021). "Tracking Control with Aperiodic Sampling over Networks with Delay and Dropout". International Journal of Systems Science 52 (10): 1987-2002. doi:10.1080/00207721.2021.1874074. 

it:Teorema del valore iniziale