LMIs in Control/pages/CT-SOFS

LMIs in Control/pages/CT-SOFS

In view of applications, static feedback of the full state is not feasible in general: only a few of the state variables (or a linear combination of them, $y=Cx(t)$ , called the output) can be actually measured and re-injected into the system.
So, we are led to the notion of static output feedback

The System

Consider the continuous-time LTI system, with generalized state-space realization $(A,B,C,0)$ {\begin{aligned}{\dot {x}}(t)&=Ax(t)+Bu(t)\\y(t)&=Cx(t)\\\end{aligned}} The Data

• $A\in \mathbb {R} ^{n\times n},B\in \mathbb {R} ^{n\times m},C\in \mathbb {R} ^{p\times n}$ • $x\in \mathbb {R} ^{n},y\in \mathbb {R} ^{p},u\in \mathbb {R} ^{m}$ The Optimization Problem

This system is static output feedback stabilizable (SOFS) if there exists a matrix F such that the closed-loop system
${\dot {x}}=(A-BKC)x$ (obtained by replacing $u=-Ky$ which means applying static output feedback)
is asymptotically stable at the origin

The LMI: LMI for Continuous Time - Static Output Feedback Stabilizability

The system is static output feedback stabilizable if and only if it satisfies any of the following conditions:

• There exists a $K\in \mathbb {R} ^{m\times p}$ and $P\in \mathbb {S} ^{n}$ , where $P>0$ , such that

${\begin{bmatrix}A^{T}P+PA-PBB^{T}P&PB+C^{T}K^{T}\\KC+B^{T}P&-1\end{bmatrix}}$ {\begin{aligned}<0\end{aligned}} • There exists a $K\in \mathbb {R} ^{m\times p}$ and $Q\in \mathbb {S} ^{n}$ , where $Q>0$ , such that

${\begin{bmatrix}QA^{T}+AQ-QC^{T}CQ&BK+QC^{T}\\CQ^{T}+K^{T}B^{T}&-1\end{bmatrix}}$ {\begin{aligned}<0\end{aligned}} • There exists a $K\in \mathbb {R} ^{m\times p}$ and $Q\in \mathbb {S} ^{n}$ , where $Q>0$ , such that

${\begin{bmatrix}QA^{T}+AQ-BB^{T}&B+QC^{T}K^{T}\\B^{T}+KCQ^{T}&-1\end{bmatrix}}$ {\begin{aligned}<0\end{aligned}} • There exists a $K\in \mathbb {R} ^{m\times p}$ and $P\in \mathbb {S} ^{n}$ , where $P>0$ , such that

${\begin{bmatrix}A^{T}P+PA-C^{T}C&PBK+C^{T}\\K^{T}B^{T}P&-1\end{bmatrix}}$ {\begin{aligned}<0\end{aligned}} Conclusion

On implementation and optimization of the above LMI using YALMIP and MOSEK (or) SeDuMi we get 2 output matrices one of which is the Symmeteric matrix $P$ (or $Q$ ) and $K$ Implementation

A link to the Matlab code for a simple implementation of this problem in the Github repository:

Related LMIs

Discrete time Static Output Feedback Stabilizability
Static Feedback Stabilizability