ArticleslgStudy

science

Stable polynomial

Stable polynomial is a science 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 Stable polynomial rather than just read about it. In short: In the context of the characteristic polynomial of a differential equation or difference equation, a polynomial is said to be stable if either: all its roots lie in the open left half-plane, or all its roots lie in the open unit disk. The first condition provides stability for continuous-time linear systems, and the second case relates to stability of discrete-time linear systems.

Key takeaways

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

Reference excerpt

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

all its roots lie in the open left half-plane, or all its roots lie in the open unit disk. 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-stable polynomial and with the second property a Schur-stable 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 The Routh–Hurwitz theorem provides an algorithm for determining if a given polynomial is Hurwitz stable, which is implemented in the Routh–Hurwitz and Liénard–Chipart tests. To test if a given polynomial P (of degree d) is Schur stable, it suffices to apply this theorem to the transformed polynomial

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

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Stable polynomial

Start with the simplest possible case. Write down what Stable polynomial claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Stable polynomial 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 Stable polynomial 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 Stable polynomial

In research
Stable polynomial appears in science 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 Stable polynomial 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
Stable polynomial is common in secondary-school and first-year university syllabi. It links to neighbouring topics Polynomials, Stability theory, so understanding it makes those chapters shorter.
In everyday life
Look for Stable polynomial 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.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Stable polynomial in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Stable polynomial 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 Stable polynomial out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Stable polynomial in simple terms?

In the context of the characteristic polynomial of a differential equation or difference equation, a polynomial is said to be stable if either: all its roots lie in the open left half-plane, or all its roots lie in the open unit disk. The first condition provides stability for continuous-time linea…

Why does Stable polynomial matter?

Because it connects several science 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 Stable polynomial?

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 Stable polynomial.

Tags

  • Polynomials
  • Stability theory

Keep exploring