Stable polynomial

A polynomial is said to be stable if either:

The first condition provides stability for (or continuous-time) linear systems, and the second case relates to stability of discrete-time linear systems. A polynomial with the first property is called at times a Hurwitz polynomial and with the second property a Schur polynomial. Stable polynomials arise in control theory and in mathematical theory of differential and difference equations. A linear, time-invariant system (see LTI system theory) is said to be BIBO stable if every bounded input produces bounded output. A linear system is BIBO stable if its characteristic polynomial is stable. The denominator is required to be Hurwitz stable if the system is in continuous-time and Schur stable if it is in discrete-time. In practice, stability is determined by applying any one of several stability criteria.

Properties

 Q(z)=(z-1)^d P\left({{z+1}\over{z-1}}\right)

obtained after the Möbius transformation z \mapsto {{z+1}\over{z-1}} which maps the left half-plane to the open unit disc: P is Schur stable if and only if Q is Hurwitz stable and  P(1)\neq 0. For higher degree polynomials the extra computation involved in this mapping can be avoided by testing the Schur stability by the Schur-Cohn test, the Jury test or the Bistritz test.

 a_n>a_{n-1}>\cdots>a_0>0,

is Schur stable.

Examples

 z_k=\cos\left({{2\pi k}\over 5}\right)+i \sin\left({{2\pi k}\over 5}\right), \, k=1, \ldots, 4 \ .
Note here that
 \cos({{2\pi}/5})={{\sqrt{5}-1}\over 4}>0.
It is a "boundary case" for Schur stability because its roots lie on the unit circle. The example also shows that the necessary (positivity) conditions stated above for Hurwitz stability are not sufficient.

See also

External links

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