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In mathematics, a Hurwitz polynomial, named after Adolf Hurwitz, is a polynomial whose coefficients are positive real numbers and whose roots (zeros) are located in the left half-plane of the complex plane or on the axis, that is, the real part of every root is zero or negative.[1] The term is sometimes restricted to polynomials whose roots have real parts that are strictly negative, excluding the axis (i.e., a Hurwitz stable polynomial).[2][3]

A polynomial function P(s) of a complex variable s is said to be Hurwitz if the following conditions are satisfied:

1. P(s) is real when s is real.
2. The roots of P(s) have real parts which are zero or negative.

Hurwitz polynomials are important in control systems theory, because they represent the characteristic equations of stable linear systems. Whether a polynomial is Hurwitz can be determined by solving the equation to find the roots, or from the coefficients without solving the equation by the Routh-Hurwitz stability criterion.

Examples

A simple example of a Hurwitz polynomial is the following:

The only real solution is −1, as it factors to

Properties

For a polynomial to be Hurwitz, it is necessary but not sufficient that all of its coefficients be positive. A necessary and sufficient condition that a polynomial is Hurwitz is that it pass the Routh-Hurwitz stability criterion. A given polynomial can be efficiently tested to be Hurwitz or not by using the Routh continued fraction expansion technique.

The properties of Hurwitz polynomials are:

  1. All the poles and zeros are in the left half plane or on its boundary, the imaginary axis.
  2. Any poles and zeros on the imaginary axis are simple (have a multiplicity of one).
  3. Any poles on the imaginary axis have real strictly positive residues, and similarly at any zeros on the imaginary axis, the function has a real strictly positive derivative.
  4. Over the right half plane, the minimum value of the real part of a PR function occurs on the imaginary axis (because the real part of an analytic function constitutes a harmonic function over the plane, and therefore satisfies the maximum principle).
  5. The polynomial should not have missing powers of s.

References

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