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Revision as of 23:21, 22 October 2005 editPierremenard (talk | contribs)1,093 edits clarified connection between polynomial stability and BIBO stablies; cleaned the properties section; inserted openness into the definition (common usage, though the mathworld page is sloppy with it)← Previous edit Latest revision as of 18:56, 5 November 2024 edit undoWallAdhesion (talk | contribs)Extended confirmed users921 edits →Hurwitz matrix: Disambiguated link to Hurwitz-stable matrix; MOS:SOB 
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{{Short description|Characteristic polynomial whose associated linear system is stable}}
A ] is said to be '''stable''' if either:
In the context of the ] of a ] or ], a ] is said to be '''stable''' if either:
* all its roots lie in the ] left ], or * all its roots lie in the ] left ], or
* all its roots lie in the ] ]. * all its roots lie in the ] ].


The first condition provides ] for ] linear systems, and the second case relates to stability
The first condition defines ] (or ]) stability and the second one ] (or ]) stability. Stable polynomials arise in various mathematical fields, for example in ] and ]. Indeed, a linear, ] (see ]) is said to be ] ] bounded inputs produce bounded outputs; this is equivalent to requiring that the ] of its ] (which can be proven to be rational) 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. Stable polynomials are sometimes called ]s and ]s.
of ] linear systems. A polynomial with the first property is called at times a ] and with the second property a Schur polynomial. Stable polynomials arise in ] and in mathematical theory
of differential and difference equations. A linear, ] (see ]) is said to be ] 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 ].


==Properties== ==Properties==
* The ] provides an algorithm for determining if a given polynomial is Hurwitz stable. To test if a given polynomial ''P'' (of degree ''d'') is Schur stable, it suffices to apply this theorem to the transformed polynomial * The ] provides an algorithm for determining if a given polynomial is Hurwitz stable, which is implemented in the ] and ] tests.
* To test if a given polynomial ''P'' (of ] ''d'') is Schur stable, it suffices to apply this theorem to the transformed polynomial


:<math> Q(z)=(z-1)^d P\left({{z+1}\over{z-1}}\right) ::<math> Q(z)=(z-1)^d P\left({{z+1}\over{z-1}}\right)</math>
</math>


obtained after the ] <math>z \mapsto {{z+1}\over{z-1}}</math> which maps the left half-plane to the open unit disc: ''P'' is Schur stable iff ''Q'' is Hurwitz stable. :obtained after the ] <math>z \mapsto {{z+1}\over{z-1}}</math> which maps the left half-plane to the open unit disc: ''P'' is Schur stable if and only if ''Q'' is Hurwitz stable and <math> P(1)\neq 0</math>. 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 ] or the ].


* Necessary condition: a Hurwitz stable polynomial (with real coefficients) has coefficients of the same sign (either all positive or all negative). * Necessary condition: a Hurwitz stable polynomial (with ] ]s) has coefficients of the same sign (either all positive or all negative).
⚫ * Sufficient condition: a polynomial <math>f(z) = a_0+a_1 z+\cdots+a_n z^n</math> with (real) coefficients such that
⚫ ::<math> a_n>a_{n-1}>\cdots>a_0 > 0,</math>
⚫ :is Schur stable.


⚫ * Product rule: Two polynomials ''f'' and ''g'' are stable (of the same type) if and only if the product ''fg'' is stable.
⚫ * Sufficient condition: a polynomial <math> f(z)=a_0+a_1 z+\cdots+a_n z^n</math> with (real) coefficients such that:
*Hadamard product: The Hadamard (coefficient-wise) product of two Hurwitz stable polynomials is again Hurwitz stable.<ref>{{Cite journal|last=Garloff|first=Jürgen|last2=Wagner|first2=David G.|date=1996|title=Hadamard Products of Stable Polynomials Are Stable|journal=Journal of Mathematical Analysis and Applications|language=en|volume=202|issue=3|pages=797–809|doi=10.1006/jmaa.1996.0348|doi-access=free}}</ref>
⚫ :<math> a_n>a_{n-1}>\cdots>a_0>0,</math>
⚫ is Schur stable.

⚫ * Product rule: Two polynomials ''f'' and ''g'' are stable (of the same type) iff the product ''fg'' is stable.


==Examples== ==Examples==
* <math> 4z^3+3z^2+2z+1 </math> is Schur stable because it satisfies the sufficient condition; * <math> 4z^3+3z^2+2z+1 </math> is Schur stable because it satisfies the sufficient condition;
* <math> z^{10}</math> is Schur stable (because all its roots equal 0) but it does not satisfy the sufficient condition; * <math> z^{10}</math> is Schur stable (because all its roots equal 0) but it does not satisfy the sufficient condition;
* <math> z^2-z-2</math> is not Hurwitz stable (its roots are -1,2) because it violates the necessary condition; * <math> z^2-z-2</math> is not Hurwitz stable (its roots are −1 and 2) because it violates the necessary condition;
* <math> z^2+3z+2 </math> is Hurwitz stable (its roots are -1,-2). * <math> z^2+3z+2 </math> is Hurwitz stable (its roots are −1 and −2).
* The polynomial <math> z^4+z^3+z^2+z+1 </math> (with positive coefficients) is neither Hurwitz stable nor Schur stable. Its roots are the four primitive fifth roots of unity * The polynomial <math> z^4+z^3+z^2+z+1 </math> (with positive coefficients) is neither Hurwitz stable nor Schur stable. Its roots are the four primitive fifth ]


::<math> z_k=\cos\left({{2\pi k}\over 5}\right)+i \sin\left({{2\pi k}\over 5}\right), \, k=1, \ldots, 4 \ .</math> ::<math> z_k=\cos\left({{2\pi k}\over 5}\right)+i \sin\left({{2\pi k}\over 5}\right), \, k=1, \ldots, 4\, .</math>


:Note here that :Note here that


::<math> \cos({{2\pi}/5})={{\sqrt{5}-1}\over 4}>0. ::<math> \cos({{2\pi}/5})={{\sqrt{5}-1}\over 4}>0.
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: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. :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.

== Stable matrices ==
Just as stable polynomials are crucial for assessing the stability of systems described by polynomials, stability matrices play a vital role in evaluating the stability of ].

=== Hurwitz matrix ===
{{Main|Hurwitz-stable matrix}}
A ] ''A'' is called a '''Hurwitz matrix''' if every ] of ''A'' has strictly negative ].

=== Schur matrix ===
'''Schur matrices''' is an analogue of the Hurwitz matrices for discrete-time systems. A matrix ''A'' is a Schur (stable) matrix if its eigenvalues are located in the ] in the ].


==See also== ==See also==
* ] * ]
* ]
* ]

==References==
{{Reflist}}

==External links== ==External links==
* *


] ]
] ]

]

Latest revision as of 18:56, 5 November 2024

Characteristic polynomial whose associated linear system is stable

In the context of the characteristic polynomial of a differential equation or difference equation, a polynomial is said to be stable if either:

The first condition provides stability for 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 ( z + 1 z − 1 ) {\displaystyle Q(z)=(z-1)^{d}P\left({{z+1} \over {z-1}}\right)}
obtained after the Möbius transformation z ↦ z + 1 z − 1 {\displaystyle 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 ) ≠ 0 {\displaystyle 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.
  • Necessary condition: a Hurwitz stable polynomial (with real coefficients) has coefficients of the same sign (either all positive or all negative).
  • Sufficient condition: a polynomial f ( z ) = a 0 + a 1 z + ⋯ + a n z n {\displaystyle f(z)=a_{0}+a_{1}z+\cdots +a_{n}z^{n}} with (real) coefficients such that
a n > a n − 1 > ⋯ > a 0 > 0 , {\displaystyle a_{n}>a_{n-1}>\cdots >a_{0}>0,}
is Schur stable.
  • Product rule: Two polynomials f and g are stable (of the same type) if and only if the product fg is stable.
  • Hadamard product: The Hadamard (coefficient-wise) product of two Hurwitz stable polynomials is again Hurwitz stable.

Examples

  • 4 z 3 + 3 z 2 + 2 z + 1 {\displaystyle 4z^{3}+3z^{2}+2z+1} is Schur stable because it satisfies the sufficient condition;
  • z 10 {\displaystyle z^{10}} is Schur stable (because all its roots equal 0) but it does not satisfy the sufficient condition;
  • z 2 − z − 2 {\displaystyle z^{2}-z-2} is not Hurwitz stable (its roots are −1 and 2) because it violates the necessary condition;
  • z 2 + 3 z + 2 {\displaystyle z^{2}+3z+2} is Hurwitz stable (its roots are −1 and −2).
  • The polynomial z 4 + z 3 + z 2 + z + 1 {\displaystyle z^{4}+z^{3}+z^{2}+z+1} (with positive coefficients) is neither Hurwitz stable nor Schur stable. Its roots are the four primitive fifth roots of unity
z k = cos ⁡ ( 2 π k 5 ) + i sin ⁡ ( 2 π k 5 ) , k = 1 , … , 4 . {\displaystyle 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 π / 5 ) = 5 − 1 4 > 0. {\displaystyle \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.

Stable matrices

Just as stable polynomials are crucial for assessing the stability of systems described by polynomials, stability matrices play a vital role in evaluating the stability of systems represented by matrices.

Hurwitz matrix

Main article: Hurwitz-stable matrix

A square matrix A is called a Hurwitz matrix if every eigenvalue of A has strictly negative real part.

Schur matrix

Schur matrices is an analogue of the Hurwitz matrices for discrete-time systems. A matrix A is a Schur (stable) matrix if its eigenvalues are located in the open unit disk in the complex plane.

See also

References

  1. Garloff, Jürgen; Wagner, David G. (1996). "Hadamard Products of Stable Polynomials Are Stable". Journal of Mathematical Analysis and Applications. 202 (3): 797–809. doi:10.1006/jmaa.1996.0348.

External links

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