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Routh–Hurwitz theorem

Routh–Hurwitz theorem is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Routh–Hurwitz theorem rather than just read about it. In short: In mathematics, the Routh–Hurwitz theorem gives a test to determine whether all roots of a given polynomial lie in the left-half complex plane. Polynomials with this property are called Hurwitz stable polynomials.

Key takeaways

  • Routh–Hurwitz theorem belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Routh–Hurwitz theorem to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Routh–Hurwitz theorem from memory before moving on to harder problems.

Reference excerpt

In mathematics, the Routh–Hurwitz theorem gives a test to determine whether all roots of a given polynomial lie in the left-half complex plane. Polynomials with this property are called Hurwitz stable polynomials. The Routh–Hurwitz theorem is important in dynamical systems and control theory, because the characteristic polynomial of the differential equations of a stable, linear system has roots limited to the left half plane (negative eigenvalues). Thus the theorem provides a mathematical test, the Routh–Hurwitz stability criterion, to determine whether a linear dynamical system is stable without solving the system. The Routh–Hurwitz theorem was proved in 1895, and it was named after Edward John Routh and Adolf Hurwitz.

Notations Let f(z) be a polynomial (with complex coefficients) of degree n with no roots on the imaginary axis (i.e. the line z = ic where i is the imaginary unit and c is a real number). Let us define real polynomials P0(y) and P1(y) by f(iy) = P0(y) + iP1(y), respectively the real and imaginary parts of f on the imaginary line. Furthermore, let us denote by:

p the number of roots of f in the left half-plane (taking into account multiplicities); q the number of roots of f in the right half-plane (taking into account multiplicities); Δ arg f(iy) the variation of the argument of f(iy) when y runs from −∞ to +∞; w(x) is the number of variations of the generalized Sturm chain obtained from P0(y) and P1(y) by applying the Euclidean algorithm; I+∞−∞ r is the Cauchy index of the rational function r over the real line.

Statement With the notations introduced above, the Routh–Hurwitz theorem states that:

p − q = 1 π Δ arg ⁡ f ( i y ) = { + I − ∞ + ∞ P 0 ( y ) P 1 ( y ) for odd degree − I − ∞ + ∞ P 1 ( y ) P 0 ( y ) for even degree } = w ( + ∞ ) − w ( − ∞ ) . {\displaystyle p-q={\frac {1}{\pi }}\Delta \arg f(iy)=\left.{\begin{cases}+I_{-\infty }^{+\infty }{\frac {P_{0}(y)}{P_{1}(y)}}&{\text{for odd degree}}\\[10pt]-I_{-\infty }^{+\infty }{\frac {P_{1}(y)}{P_{0}(y)}}&{\text{for even degree}}\end{cases}}\right\}=w(+\infty )-w(-\infty ).}

From the first equality we can for instance conclude that when the variation of the argument of f(iy) is positive, then f(z) will have more roots to the left of the imaginary axis than to its right. The equality p − q = w(+∞) − w(−∞) can be viewed as the complex counterpart of Sturm's theorem. Note the differences: in Sturm's theorem, the left member is p + q and the w from the right member is the number of variations of a Sturm chain (while w refers to a generalized Sturm chain in the present theorem).

Routh–Hurwitz stability criterion

We can easily determine a stability criterion using this theorem as it is trivial that f(z) is Hurwitz-stable if and only if p − q = n. We thus obtain conditions on the coefficients of f(z) by imposing w(+∞) = n and w(−∞) = 0.

See also Plastic ratio

References

Routh, E. J. (1877). A Treatise on the Stability of a Given State of Motion, Particularly Steady Motion. Macmillan and co. Hurwitz, A. (1964). "On The Conditions Under Which An Equation Has Only Roots With Negative Real Parts". In Bellman, Richard; Kalaba, Robert E. (eds.). Selected Papers on Mathematical Trends in Control Theory. New York: Dover. Gantmacher, F. R. (2005) [1959]. Applications of the Theory of Matrices. New York: Dover. pp. 226–233. ISBN 0-486-44554-2. Rahman, Q. I.; Schmeisser, G. (2002). Analytic theory of polynomials. London Mathematical Society Monographs. New Series. Vol. 26. Oxford: Oxford University Press. ISBN 0-19-853493-0. Zbl 1072.30006. Explaining the Routh–Hurwitz Criterion (2020)

External links Mathworld entry

Worked examples

Example 1 — a first encounter with Routh–Hurwitz theorem

Start with the simplest possible case. Write down what Routh–Hurwitz theorem claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Routh–Hurwitz theorem before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Routh–Hurwitz theorem ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Routh–Hurwitz theorem

In research
Routh–Hurwitz theorem appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Routh–Hurwitz theorem in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Routh–Hurwitz theorem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Theorems about polynomials, Theorems in complex analysis, Theorems in real analysis, so understanding it makes those chapters shorter.
In everyday life
Look for Routh–Hurwitz theorem outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Routh–Hurwitz theorem in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Routh–Hurwitz theorem means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Routh–Hurwitz theorem out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Routh–Hurwitz theorem in simple terms?

In mathematics, the Routh–Hurwitz theorem gives a test to determine whether all roots of a given polynomial lie in the left-half complex plane. Polynomials with this property are called Hurwitz stable polynomials.

Why does Routh–Hurwitz theorem matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Routh–Hurwitz theorem?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Routh–Hurwitz theorem.

Tags

  • Theorems about polynomials
  • Theorems in complex analysis
  • Theorems in real analysis

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