LMIs in Control/pages/systemzeroswithout feedthrough

Let's say we have a transfer function defined as a ratio of two polynomials: ${\begin{aligned}H(s)={\frac {N(s)}{D(s)}}\\\end{aligned}}$ Zeros are the roots of N(s) (the numerator of the transfer function) obtained by setting $N(s)=0$ and solving for s.The values of the poles and the zeros of a system determine whether the system is stable, and how well the system performs. Similarly, the system zeros are either real or appear in complex conjugate pairs. In the case of system zeros without feedthrough, we take the assumption that $D=0$.

The System

Consider a continuous-time LTI system, $G$ , with minimal statespace representation $(A,B,C,0)$

${\begin{aligned}{\dot {x}}(t)=Ax(t)+Bu(t)\\y(t)=Cx(t)\end{aligned}}$

The Data

The matrices:

${\begin{aligned}A\in \mathbb {R} ^{n\times n}\\M\in \mathbb {R} ^{n\times q}\\N\in \mathbb {R} ^{q\times n}\\\end{aligned}}$

The LMI: System Zeros without feedthrough

The transmission zeros of $G(s)=C(sI-A)^{-}1B$ are the eigenvalues of $NAM$, where $N\in \mathbb {R} ^{q\times n},M\in \mathbb {R} ^{n\times q},CM=0,NB=0,NM=1.$. Therefore , $G(s)$ is a minimum phase if and only if there exists $P\in \mathbb {S} ^{q}$, where $P>0$ such that

${\begin{aligned}PNAM+M^{T}A^{T}N^{T}P<0\end{aligned}}$

Conclusion:

If P exists, it ensures non-minimum phase. Eigenvalues of NAM then gives the zeros of the system.

Implementation

https://github.com/Ricky-10/coding107/blob/master/Systemzeroswithoutfeedthrough

External Links

A list of references documenting and validating the LMI.

• LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
• LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
• LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
• Control_Systems/Poles_and_Zeros