# LMIs in Control/Stability Analysis/Continuous Time/Quadratic Stability Margins

LMIs in Control/Stability Analysis/Continuous Time/Quadratic Stability Margins

{\displaystyle {\begin{aligned}{\text{The quadratic stability margin of the system is defined as the largest }}\alpha \geq 0{\text{ for which the system is quadratically stable.}}{\text{This LMI applies for systems with norm-bounded uncertainty.}}\end{aligned}}}

## The System

{\displaystyle {\begin{aligned}{\dot {x}}(t)&=Ax(t)+B_{p}p(t),&&p^{T}p\leq \alpha ^{2}x^{T}C_{q}^{T}C_{q}x\\\end{aligned}}}

## The Data

The matrices ${\displaystyle A,B_{p},C_{q}}$.

## The Optimization Problem

${\displaystyle {\text{Maximize }}\beta =\alpha ^{2}{\text{ subject to the LMI constraint.}}}$

## The LMI:

{\displaystyle {\begin{aligned}{\text{Find}}\;&P,\lambda ,{\text{ and }}\beta =\alpha ^{2}:\\{\begin{bmatrix}A^{T}P+PA+\beta \lambda C_{q}^{T}C_{q}&PB_{p}\\B_{p}^{T}P&-\lambda I\end{bmatrix}}<0\\\end{aligned}}}

## Conclusion:

If there exists an ${\displaystyle \alpha \geq 0}$ then the system is quadratically stable, and the stability margin is the largest such ${\displaystyle \alpha }$.