LMIs in Control/Matrix and LMI Properties and Tools/Passivity and Bounded Realness

This section deals with passivity of a system.

The System

Given a state-space representation of a linear system

$\begin{array}{c}\dot{x}=Ax+Bu\\ y=Cx+Du\\ \end{array}$

$x\in {ℝ}^n,y\in {ℝ}^m,u\in {ℝ}^r$ are the state, output and input vectors respectively.

The Data

$A,B,C,D$ are system matrices.

Definition

The linear system with the same number of input and output variables is called passive if Template:NumBlk

hold for any arbitrary $T\ge 0$, arbitrary input $u(t)$, and the corresponding solution $y(t)$ of the system with $x(0)=0$. In addition, the transfer function matrix Template:NumBlk

of system is called is positive real if it is square and satisfies

LMI Conditon

Let the linear system be controllable. Then, the system is passive if an only if there exists $P>0$ such that Template:NumBlk

Implementation

This implementation requires Yalmip and Mosek.

• https://github.com/NoobMasterLoki/LMI--master/blob/main/Passivity.m

Conclusion:

Thus, it is seen that passivity and positive-realness describe the same property of a linear system, one gives the time-domain feature and the other provides frequency-domain feature of this property.

External Links

• LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
• LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
• LMIs in Control Systems: Analysis, Design and Applications - by Guang-Ren Duan and Hai-Hua Yu, CRC Press, Taylor & amp; Francis Group, 2013