动态系统的建模与分析

前言

CS小菜鸡控制理论入门
视频学习笔记
视频传送门:动态系统的建模与分析】9_一阶系统的频率响应_低通滤波器_Matlab/Simulink分析

拉普拉斯变换

F ( s ) = L { f ( t ) } = ∫ 0 ∞ f ( t ) e − s t d t F(s)=\mathcal{L}\{f(t)\}=\int_0^\infty f(t)e^{-st}\mathrm{d}t F(s)=L{ f(t)}=0f(t)estdt,其中 s = σ + j ω s=\sigma+j\omega s=σ+

L { f ′ ( t ) } = s F ( s ) − f ( 0 ) \mathcal{L}\{f'(t)\}=sF(s)-f(0) L{ f(t)}=sF(s)f(0)

L { f ′ ′ ( t ) } = s 2 F ( s ) − s f ( 0 ) − f ′ ( 0 ) \mathcal{L}\{f''(t)\}=s^2F(s)-sf(0)-f'(0) L{ f′′(t)}=s2F(s)sf(0)f(0)

L { ∫ 0 t f ( τ ) d ( τ ) } = 1 s F ( s ) \mathcal{L}\{\int_0^t f(\tau)d(\tau)\}=\frac{1}{s}F(s) L{ 0tf(τ)d(τ)}=s1F(s)

一个电路例子:

e ′ = L i ′ ′ + R i ′ + 1 c i e'=Li''+Ri'+\frac{1}{c}i e=Li′′+Ri+c1i

s E ( s ) = L s 2 I ( s ) + R s I ( s ) + 1 c I ( s ) sE(s)=Ls^2I(s)+RsI(s)+\frac{1}{c}I(s) sE(s)=Ls2I(s)+RsI(s)+c1I(s)

s E ( s ) = ( L s 2 + R s + 1 c ) I ( s ) sE(s)=(Ls^2+Rs+\frac{1}{c})I(s) sE(s)=(Ls2+Rs+c1)I(s)

I ( s ) = s L s 2 + R s + 1 c E ( s ) I(s)=\frac{s}{Ls^2+Rs+\frac{1}{c}}E(s) I(s)=Ls2+Rs+c1sE(s)

常系数微分方程    ⟺    \iff 线性时不变系统

非线性化系统:1.在平衡点处线性化 2.采用非线性化分析控制

拉普拉斯变换求解线性微分方程:

  1. 运用 L \mathcal{L} L t t t域转化到 s s s域;
  2. + − × ÷ +-\times \div +×÷
  3. 运用 L − 1 \mathcal{L^{-1}} L1 s s s域转化到 t t t域;
拉普拉斯逆变换

F ( s ) = 5 − s s 2 + 5 s + 4 F(s)=\frac{5-s}{s^2+5s+4} F(s)=s2+5s+45s

F ( s ) = − 3 s + 4 + 2 s + 1 F(s)=\frac{-3}{s+4}+\frac{2}{s+1} F(s)=s+43+s+12

L − 1 [ F ( s ) ] = − 3 e − 4 t + 2 e − t \mathcal{L^{-1}}[F(s)]=-3e^{-4t}+2e^{-t} L1[F(s)]=3e4t+2et

s = − 4 , − 1 s=-4,-1 s=4,1:传递函数(Transfer Function)的极点(Poles)

一阶系统的单位阶跃响应(Step Response)

x ˙ ( t ) + g R x ( t ) = u ( t ) \dot{x}(t)+\frac{g}{R}x(t)=u(t) x˙(t)+Rgx(t)=u(t)

x ( t ) = C R g ( 1 − e − g R t ) x(t)=\frac{CR}{g}(1-e^{-\frac{g}{R}t}) x(t)=gCR(1eRgt)

时间常数 t = τ t=\tau t=τ,满足 x ( τ ) = 1 − 1 e = 0.63 x(\tau)=1-\frac{1}{e}=0.63 x(τ)=1e1=0.63

稳定(整定)时间 T s s = 4 τ Tss=4\tau Tss=4τ

用于系统辨识:

假设 T s s = 4 Tss=4 Tss=4,则 τ = 1 = R g \tau=1=\frac{R}{g} τ=1=gR

C R g = 5 ⟹ C = 5 \frac{CR}{g}=5\Longrightarrow C=5 gCR=5C=5

u ( s ) ⟶ a s + a ⟶ x ( s ) u(s) \longrightarrow \frac{a}{s+a} \longrightarrow x(s) u(s)s+aax(s):本质上是一个低通滤波器

频率响应

input: M i s i n ( ω t + ϕ i ) M_isin(\omega t+\phi_i) Misin(ωt+ϕi)

output: M 0 s i n ( ω t + ϕ 0 ) M_0sin(\omega t+\phi_0) M0sin(ωt+ϕ0)

振幅响应: M 0 M i = M \frac{M_0}{M_i}=M MiM0=M

幅角响应: ϕ 0 − ϕ i = ϕ \phi_0-\phi_i=\phi ϕ0ϕi=ϕ

(一番数学推导…)

conclusion

M G = ∣ G ( j ω ) ∣ M_G=|G(j\omega)| MG=G()

ϕ G = ∠ G ( j ω ) \phi_G=\angle G(j\omega) ϕG=G()

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转载自blog.csdn.net/qq_23096319/article/details/129189540
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