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Lyapunov equation : ウィキペディア英語版
Lyapunov equation
In control theory, the discrete Lyapunov equation is of the form
:A X A^ - X + Q = 0
where Q is a Hermitian matrix and A^H is the conjugate transpose of A. The continuous Lyapunov equation is of form
:AX + XA^H + Q = 0.
The Lyapunov equation occurs in many branches of control theory, such as stability analysis and optimal control. This and related equations are named after the Russian mathematician Aleksandr Lyapunov.
==Application to stability==
In the following theorems A, P, Q \in \mathbb^, and P and Q are symmetric. The notation P>0 means that the matrix P is positive definite.
Theorem (continuous time version). Given any Q>0, there exists a unique P>0 satisfying A^T P + P A + Q = 0 if and only if the linear system \dot=A x is globally asymptotically stable. The quadratic function V(z)=z^T P z is a Lyapunov function that can be used to verify stability.
Theorem (discrete time version). Given any Q>0, there exists a unique P>0 satisfying A^T P A -P + Q = 0 if and only if the linear system x(t+1)=A x(t) is globally asymptotically stable. As before, z^T P z is a Lyapunov function.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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