LMIs in Control/Stability Analysis/Continuous Time/Hurwitz Stabilizability

This section studies the stabilizability properties of the control systems.

The System

Given a state-space representation of a linear system

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

Where $\rho$ represents the differential operator ( when the system is continuous-time) or one-step forward shift operator ( Discrete-Time system). $x\in {ℝ}^n,y\in {ℝ}^m,u\in {ℝ}^r$ are the state, output and input vectors respectively.

The Data

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

Definition

The system , or the matrix pair $(A,B)$ is Hurwitz Stabilizable if there exists a real matrix $K$ such that $(A+BK)$ is Hurwitz Stable. The condition for Hurwitz Stabilizability of a given matrix pair (A,B) is given by the PBH criterion: Template:NumBlk

The PBH criterion shows that the system is Hurwitz stabilizable if all uncontrollable modes are Hurwitz stable.

LMI Condition

The system, or matrix pair $(A,B)$ is Hurwitz stabilizable if and only if there exists symmetric positive definite matrix $P$ and $W$ such that: Template:NumBlk

Following definition of Hurwitz Stabilizability and Lyapunov Stability theory, the PBH criterion is true if and only if , a matrix $K$ and a matrix $P>0$ satisfying: Template:NumBlk

Letting Template:NumBlk

Putting (4) in (3) gives us (2).

Implementation

This implementation requires Yalmip and Mosek.

• https://github.com/ShenoyVaradaraya/LMI--master/blob/main/Hurwitz_Stabilizability.m

Conclusion

Compared with the second rank condition, LMI has a computational advantage while also maintaining numerical reliability.

References

• 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 & Francis Group, 2013