LMIs in Control/Click here to continue/LMIs in system and stability Theory/KYP Lemma for Descriptor systems

The Concept
Descriptor system descriptions frequently appear when solving computational problems in the analysis and design of standard linear systems. The numerically reliable solution of many standard control problems like the solu­tion of Riccati equations, computation of system zeros, design of fault detection and isolation filters (FDI), etc. relies on using descriptor system techniques.

Many algorithm for standard systems as for example stabilization techniques, factorization methods, minimal realization, model reduction, etc. have been extended to the more general descriptor system descriptions. An important application of these algorithms is the numeri­cally reliable computation with rational and polynomial matrices via equivalent descriptor representations. Recall that each rational matrix R(s) can be seen as the transfer-function matrix of a continuous- or discrete-time descriptor system. Thus, each R(s) can be equivalently realized by a descriptor system quadruple (A-sE, B, C, D) satisfying R(S)= C(SE-A)-1B+D

Many operations on standard matrices (e.g., finding the rank, determinant, inverse or generalized inverses), or the solution of linear matrix equa­tions can be performed for rational matrices as well using descriptor system techniques. Other important applications of descriptor techniques are the computation of inner-outer and spectral factorisations, or minimum degree and normal­ized coprime factorisations of polynomial and rational matrices. More explanation can be found in the website of Institute of System Dynamics and control

The System
Consider a square, contiuous-time linear time-invariant (LTI) system, $$\mathcal{G} : \mathcal{L}_{2e} \rightarrow \mathcal{L}_{2e}$$, with minimal state-space relization (E, A, B, C, D), where $$\mathcal{E, A} \in \mathcal{R}^{n\times n}, \mathcal{B} \in \mathcal{R}^{n\times m}, \mathcal{C} \in \mathcal{R}^{p\times n},$$ and $$\mathcal{D} \in \mathcal{R}^{p\times m} $$.



\begin{align} E\dot x(t)&=Ax(t)+Bu(t),\\ y(t)&=Cx(t)+Du(t)\\ \end{align}$$

The Data
The matrices The matrices $$ E, A,B,C $$ and $$D $$

LMI : KYP Lemma for Descriptor Systems
The system $$\mathcal{G}$$ is extended strictly positive real (ESPR) if and only if there exists $$ X \in \mathcal{R}^{n\times n} $$ and $$ W \in \mathcal{R}^{n\times m}$$ such that
 * $$ E^{T}X = X^{T}E \ge 0$$
 * $$ E^{T}W = 0 $$
 * $$\begin{bmatrix}

X^{T}A + A^{T}X &  A^{T}W + X^{T}B - C^{T}  \\ (A^{T}W + X^{T}B - C^{T})^{T} &  W^{T}B + B^{T}W - (D^{T} + D) \end{bmatrix} < 0.$$

The system is also ESPR if there exists $$ \mathcal{X} \in \mathcal{R}^{n\times n} $$ such that
 * $$ E^{T}X = X^{T}E \ge 0$$
 * $$\begin{bmatrix}

X^{T}A + A^{T}X &  X^{T}B - C^{T}  \\ (X^{T}B - C^{T})^{T} &  -(D^{T} + D) \end{bmatrix} < 0.$$

Conclusion:
If there exist a X and W matrix satisfying above LMIs then the system $$\mathcal{G}$$ is Extended Strictly Positive Real.

Implementation
Code for implementation of this LMI using MATLAB. https://github.com/VJanand25/LMI

Related LMIs
KYP Lemma State Space Stability Discrete Time KYP Lemma with Feedthrough