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Self control principle learning notes - system stability analysis (1) - BIBO stability and Routh criterion
2022-07-27 19:03:00 【Miracle Fan】
Self control principle learning notes
Self control principle learning notes column
1. The input and output are stable - about CLTIS
1.1 Two steady states
1.1.1 BIBO Stable
Definition : If a system is subjected to a bounded input or disturbance, its response is finite .
necessary and sufficient condition :
y ( t ) = ∫ 0 t g ( τ ) u ( t − τ ) d τ ⇒ ∣ y ( t ) ∣ ≤ ∫ 0 t ∣ g ( τ ) ∣ ⋅ ∣ u ( t − τ ) ∣ d τ ≤ M ∫ 0 t ∣ g ( τ ) ∣ d τ y(t)=\int_0^tg(\tau)u(t-\tau)d\tau\Rightarrow |y(t)|\le \int _0^t|g(\tau)|\cdot |u(t-\tau)|d\tau \le M\int_0^t|g(\tau)|d\tau y(t)=∫0tg(τ)u(t−τ)dτ⇒∣y(t)∣≤∫0t∣g(τ)∣⋅∣u(t−τ)∣dτ≤M∫0t∣g(τ)∣dτ
If you want to make y(t) bounded , Then the necessary and sufficient condition is ∣ g ( τ ) ∣ |g(\tau)| ∣g(τ)∣ Absolutely integrableNon integrable examples : g ( t ) = 1 t − 1 g(t)=\frac{1}{t-1} g(t)=t−11
about CLTIS, Satisfy BIBO Then there is only the pole of the left half plane :
Assume that the transfer function is impulse response Laplace Transformation , therefore :
G ( s ) = ∫ 0 ∞ g ( t ) e − s t d t ⇒ ∣ G ( s ) ∣ ≤ ∫ 0 ∞ ∣ g ( t ) ∣ ⋅ ∣ e − s t ∣ d t = ∫ 0 ∞ ∣ g ( t ) ∣ ⋅ ∣ e − σ t ∣ d t * i f σ ≥ 0 , ∣ G ( s ) ∣ ∣ s = σ + i w → ∞ ≤ ∫ 0 ∞ ∣ g ( t ) ∣ ⋅ ∣ e − σ t ∣ d t ≤ ∫ 0 ∞ ∣ g ( t ) ∣ d t G(s)=\int_0^\infty g(t)e^{-st}dt\Rightarrow|G(s)|\le\int_0^\infty |g(t)|\cdot|e^{-st}|dt=\int_0^\infty|g(t)|\cdot|e^{-\sigma t}|dt\\ \Longrightarrow if \quad\sigma \ge 0,\quad |G(s)||_{s=\sigma+iw}\rightarrow\infty\le\int^\infty_0|g(t)|\cdot|e^{-\sigma t}|dt\le\int_0^\infty|g(t)|dt G(s)=∫0∞g(t)e−stdt⇒∣G(s)∣≤∫0∞∣g(t)∣⋅∣e−st∣dt=∫0∞∣g(t)∣⋅∣e−σt∣dt*ifσ≥0,∣G(s)∣∣s=σ+iw→∞≤∫0∞∣g(t)∣⋅∣e−σt∣dt≤∫0∞∣g(t)∣dt
∣ g ( t ) ∣ |g(t)| ∣g(t)∣ unbounded , And BIBO Stabilize contradictions , All only when σ < 0 \sigma<0 σ<0, Meet the conditions .
1.1.2 Zero input stability ( Asymptotic stability )
- Definition : When t It goes to infinity , The response produced by the initial conditions tends to 0.
- Sufficient and necessary conditions for stability :
- about ∀ s i , R e ( s i ) < 0 when , C L T I S gradually near steady set \forall s_i,Re(s_i)<0 when ,CLTIS Asymptotic stability ∀si,Re(si)<0 when ,CLTIS gradually near steady set
- R e ( s i ) > 0 ∣ ∣ There are multiple virtual roots , C L T I S No steady set Re(s_i)>0||\text{ There are multiple virtual roots },CLTIS unstable Re(si)>0∣∣ There are multiple virtual roots ,CLTIS No steady set
- There are only single virtual roots , other R e ( s j ) < 0 Re(s_j)<0 Re(sj)<0,LTIS Critical delimitation .
- Related examples :
1.1.3 Stability related instructions
- about LTIS,BIBO、 Zero input stability requires eigenvalues to be located on the left of the complex plane
- about LTIS, Stability only depends on the inherent properties of the system ( The eigenvalue ), It has nothing to do with external conditions .
- Stability has a local characteristic ( Multiple stable points ), But only in time-varying systems and nonlinear systems , Time invariant systems are global .
2. Routh-Hurwitz The criterion
2.1 CLTIS Necessary conditions for stability
All coefficients of the characteristic equation of the system are greater than 0
2.2 Routh The criterion
List some Routh surface
s n a n a n − 2 a n − 4 … s^n\quad a_n \quad a_{n-2}\quad a_{n-4} \quad \dots snanan−2an−4…
s n − 1 a n − 1 a n − 3 a n − 5 … s^{n-1}\quad a_{n-1} \quad a_{n-3}\quad a_{n-5} \quad \dots sn−1an−1an−3an−5…
s n − 2 b 1 b 2 b 3 … s^{n-2}\quad b_1 \quad b_2\quad b_3 \dots sn−2b1b2b3…
s n − 3 c 1 c 2 … s^{n-3}\quad c_1 \quad c_2\quad \dots sn−3c1c2…
…………
s 0 h 1 s^0 \quad h_1 s0h1
Conventional calculation
b 1 = − [ a n a n − 2 a n − 1 a n − 3 ] a n − 1 b 2 = − [ a n a n − 4 a n − 1 a n − 5 ] a n − 1 c 1 = − [ a n − 1 a n − 3 b 1 b 2 ] b 1 c 2 = − [ a n − 1 a n − 5 b 1 b 3 ] b 1 b_1=-\frac{ \begin{bmatrix} a_{n}& a_{n-2} \\ a_{n-1}& a_{n-3} \end{bmatrix} } {a_{n-1}} \quad b_2=-\frac{ \begin{bmatrix} a_{n}& a_{n-4} \\ a_{n-1}& a_{n-5} \end{bmatrix} } {a_{n-1}}\\ c_1=-\frac{ \begin{bmatrix} a_{n-1}& a_{n-3} \\ b_1&b_2 \end{bmatrix} } {b_1} \quad c_2=-\frac{ \begin{bmatrix} a_{n-1}& a_{n-5} \\ b_1&b_3 \end{bmatrix} } {b_1} b1=−an−1[anan−1an−2an−3]b2=−an−1[anan−1an−4an−5]c1=−b1[an−1b1an−3b2]c2=−b1[an−1b1an−5b3]Judge the stability method :
The number of changes of the coefficient symbol in the first column , That is, the characteristic root is in the right half s Number of planes
Necessary and sufficient conditions for stability : The coefficients in the first column of the table are all greater than 0
2.3 Related applications
(1) The first column coefficient is 0
Use small ϵ \epsilon ϵ Method instead of zero value term , Continue to solve according to the conventional method .
If the first column is all positive , The system is not asymptotically stable , But there are pure virtual roots , Critical stability
(2) The coefficients of a row are all 0
indicate s The plane has a real root symmetrical to the origin , Or conjugate virtual root
- Take all as 0 Previous line of , Take its coefficient as the auxiliary equation ( Only take even times )
- Derivation of auxiliary equation , The coefficient substitution is 0 That's ok
- Continue with the normal steps
- Solve the auxiliary equation to get the symmetric root
(3) Related stability problems
Use the idea of exchange .
If the realistic part is less than 2, Then set u=s+2 Put it into the equation , take u As an equation variable , To solve the .
2.4 Hurwitz The criterion

The criterion : Each stage of the principal sub formula is greater than 0
=s+2 Put it into the equation , take u As an equation variable , To solve the .
2.4 Hurwitz The criterion
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The criterion : Each stage of the principal sub formula is greater than 0
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