Stability of Polynomials: Hurwitz-Routh & Nyquist Locus Curve

In summary, the conversation discusses stability of polynomials and their corresponding differential equations in the context of transfer functions. The Routh-Hurwitz criterion is a method for determining stability without calculating the roots, and the Nyquist locus curve can be used to analyze stability and the values of the roots.
  • #1
sirijo246
3
0
1) As far as i think i understand, stability of a polynomial means; the polynomial correspond to a (its inverse laplace transform) differential equation, and the differential equations solution is dependant on the coefficiants of this polynomial? if the polynomial is unstable the solution of the corresponding differential equation has oscillations increasing towards infinity...?? this is how i understood transferfunctions, but then again we have a fraction of to polynomials and the poles, the roots of the demoninator give the values of the exponential functions power,

but when we just have a polynomial i am not shure what stality means..??


2) the hurwitz-Routh-criterion for stability, is this some kind of shortcut to see weather all the roots have negtive real parts? Or what does it prove about our polynomial?

3) The Nyquist locus curve, i know how to analyze wether the corresponding polynomial is stable, but i don't know a) how it is plotted
b) is it also telling us something about the values of the roots?

Greatful for any replies as i have my advanced mathematics exam on monday!
siri
 
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  • #2


A polynomial is not stable or unstable. Stability is a property of dynamical systems.
If a polynomial represents the denominator of the transfer function of a dynamic system, its roots are the natural frequencies of the system.
If some of the roots have positive real parts, the system is unstable.
The Routh-Hurwitz algorithm allows the determination of the number of roots with positive real parts, without calculating the value of the roots.
 
  • #3


thank you
 

1. What is the Hurwitz-Routh stability criterion?

The Hurwitz-Routh stability criterion is a mathematical method used to determine the stability of a polynomial by examining the signs of its coefficients. It states that for a polynomial to be stable, all of its coefficients must be positive. This criterion is important in control systems and stability analysis.

2. How does the Routh-Hurwitz criterion differ from the Nyquist stability criterion?

While both the Routh-Hurwitz and Nyquist stability criteria are used to determine the stability of a system, they differ in their approach. The Routh-Hurwitz criterion uses the signs of the coefficients of a polynomial to determine stability, while the Nyquist stability criterion uses the frequency response of a system to determine stability. Both methods have their advantages and are used in different applications.

3. What is the Nyquist locus curve?

The Nyquist locus curve is a graphical representation of the Nyquist stability criterion. It plots the frequency response of a system on a complex plane, with the real and imaginary components of the response represented by the x and y axes, respectively. The curve can be used to analyze the stability of a system by examining its shape and encirclements of the origin.

4. Can the Routh-Hurwitz criterion be used for higher-order polynomials?

Yes, the Routh-Hurwitz criterion can be used for polynomials of any order. However, as the order of the polynomial increases, the process becomes more complex and may be better suited for computer analysis. Additionally, the Routh-Hurwitz criterion can only determine stability, and not instability, for polynomials with an odd number of terms.

5. How is the stability of a polynomial related to the roots of its characteristic equation?

The stability of a polynomial is directly related to the roots of its characteristic equation. A polynomial is considered stable if all of its roots have negative real parts, while it is considered unstable if any of its roots have positive real parts. This relationship is important in control systems analysis, as the roots of the characteristic equation can be used to determine the stability of a system.

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