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2×2 State-Space Eigenvalues

Eigenvalues of a 2×2 system matrix A — the poles that set stability, natural frequency, and damping.

Inputdet(A − λI) = 0 ⇒ λ² − (tr A)λ + det A = 0 , λ = [tr A ± √((tr A)² − 4·det A)] / 2

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The engineering

The eigenvalues of the state matrix A are the poles of a linear time-invariant system — they alone determine the free-response modes. Real negative eigenvalues decay exponentially; a complex conjugate pair oscillates and decays; anything with a positive real part is unstable. For a 2×2 A the characteristic polynomial is just λ² − (tr A)λ + det A, so you never need a matrix routine.

Quick stability check without computing roots: a 2×2 system is stable exactly when tr A < 0 and det A > 0 (both eigenvalues in the left half-plane). When the roots are complex, ωₙ = √(det A) and ζ = −tr A / (2·ωₙ), which maps the poles straight onto the second-order damping picture. Watch the sign convention — controls texts write ẋ = Ax, so the poles are the eigenvalues of A, not −A.

Where this math comes from

The word "eigenvalue" (from German eigen, "own" or "characteristic") entered mathematics through David Hilbert's 1904 work on integral equations, but the underlying idea of a characteristic root traces back to Cauchy and Cayley in the 19th century. The characteristic equation det(A − λI) = 0 is a direct product of the matrix algebra Arthur Cayley formalized in 1858.

State-space control brought eigenvalues to the bench. Rudolf Kálmán reframed control theory around the state vector around 1960, and textbooks like Chi-Tsong Chen's Linear System Theory and Design made "the eigenvalues of A are the poles of the system" the first thing every controls student learns. For a hand-sized system the trace-determinant shortcut turns pole placement into mental arithmetic.

  1. 1858Arthur CayleyFormalizes matrix algebra and the characteristic equation.
  2. 1904David HilbertCoins 'eigenvalue' in his theory of integral equations.
  3. 1960Rudolf KálmánPuts the state vector at the center of modern control theory.
  4. 1984Chi-Tsong ChenLinear System Theory and Design codifies eigenvalues as system poles for a generation of engineers.

See the full timeline of the math behind every calculator →

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