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Independent Linear Constraint System

Definition

A linear constraint system

Ax=b\boldsymbol{A}\boldsymbol{x}=\boldsymbol{b}

with A∈Rm×n\boldsymbol{A}\in\mathbb{R}^{m\times n} has independent constraints if the rows of A\boldsymbol{A} are linearly independent, equivalently

rank⁡A=m.\operatorname{rank}\boldsymbol{A}=m.

For nonlinear equality constraints g1(x)=0,…,gm(x)=0g_1(\boldsymbol{x})=0,\ldots,g_m(\boldsymbol{x})=0, the corresponding local condition at a\boldsymbol{a} is that the gradients ∇g1(a),…,∇gm(a)\boldsymbol{\nabla} g_1(\boldsymbol{a}),\ldots,\boldsymbol{\nabla} g_m(\boldsymbol{a}) are linearly independent.


Interpretation

Independent constraints each remove a genuinely new direction. Dependent constraints repeat information and can make multiplier tests misleading.

Two panels of lines in the plane. Left: two lines with independent normal vectors meet in one point (rank 2). Right: two parallel lines with dependent normal vectors (rank 1).

On the right, the rows of A\boldsymbol{A} are dependent and rank⁡A=1\operatorname{rank}\boldsymbol{A}=1. The corresponding parallel lines either have no common solution or coincide along a whole line. On the left, the two independent constraints have rank 22 and meet at one point.

The rank counts independent rows. Equality to mm means that no constraint equation is an algebraic consequence of the others; for nonlinear constraints the same check applies to their gradients at the chosen point.


Key Results


Examples

  • The constraints x+y=1x+y=1 and 2x+2y=22x+2y=2 are dependent because the second repeats the first.
  • The constraints x+y=1x+y=1 and x−y=0x-y=0 are independent because the matrix (111−1)\begin{pmatrix}1&1\\1&-1\end{pmatrix} has rank 22.

Prerequisites

Sources

Aliases: independent constraints Keywords: independent linear constraints, linearly independent constraints, constraint rank Symbols: element of, nabla gradient, real numbers

Last updated: 17 October 2026 21:53