Frequency Domain and a la carte. See also introduction slides and frequency domain slides
Open-loop versus closed-loop
Transient and steady-state response
Stability
Total response = Natural response + Forced response
Natural response (homogeneous solution): evolution of system due to initial conditions
Forced response (particular solution): evolution of system due to input
Control objects:
Stabilize the system
Produce the desired transient response
Decrease/eliminate steady-state error
Make system “robust” to withstand disturbances and variations in parameters
Achieve optimal performance
stateDiagram-v2
direction LR
[*] --> System: r(t)
System --> End: c(t)
System as linear differential equation
graph LR
Diff{{differential equations}} -- "Laplace transform" --> Algebraic{{algebraic equations}} -- "inverse Laplace transform" --> End{{time domain solution}}
L { f ( t ) } = ∫ 0 ∞ f ( t ) − s t d t = F ( s ) \mathcal{L} \{f(t)\} = \int_0^{\infty}f(t)^{-st}dt = F(s) L { f ( t )} = ∫ 0 ∞ f ( t ) − s t d t = F ( s )
Item no. f ( t ) F ( s ) 1. δ ( t ) 1 2. u ( t ) 1 s 3. t u ( t ) 1 s 2 4. t n u ( t ) n ! s n + 1 5. e − a t u ( t ) 1 s + a 6. sin ( ω t ) u ( t ) ω s 2 + ω 2 7. cos ( ω t ) u ( t ) s s 2 + ω 2 \begin{array}{c c c} \hline \text{Item no.} & f(t) & F(s) \\ \hline 1. & \delta(t) & 1 \\ 2. & u(t) & \frac{1}{s} \\ 3. & tu(t) & \frac{1}{s^2} \\ 4. & t^n u(t) & \frac{n!}{s^{n+1}} \\ 5. & e^{-at}u(t) & \frac{1}{s + a} \\ 6. & \sin(\omega t)u(t) & \frac{\omega}{s^2 + \omega^2} \\ 7. & \cos(\omega t)u(t) & \frac{s}{s^2 + \omega^2} \\ \hline \end{array} Item no. 1. 2. 3. 4. 5. 6. 7. f ( t ) δ ( t ) u ( t ) t u ( t ) t n u ( t ) e − a t u ( t ) sin ( ω t ) u ( t ) cos ( ω t ) u ( t ) F ( s ) 1 s 1 s 2 1 s n + 1 n ! s + a 1 s 2 + ω 2 ω s 2 + ω 2 s
δ ( t ) = 0 , t ≠ 0 , ∫ 0 ∞ δ ( t ) d t = 1 \delta{(t)} = 0, \quad t \neq 0,\quad \int_0^{\infty}{\delta{(t)}}dt=1 δ ( t ) = 0 , t = 0 , ∫ 0 ∞ δ ( t ) d t = 1
example: Given a unit step function u ( t ) = { 0 t < 0 1 t ≥ 0 u(t) = \begin{cases} 0 & t < 0 \\ 1 & t \ge 0 \end{cases} u ( t ) = { 0 1 t < 0 t ≥ 0
U ( s ) = L { u ( t ) } = ∫ 0 ∞ u ( t ) e − s t d t = − 1 s e − s t d t U ( s ) = − 1 s ( 0 − 1 ) = 1 s \begin{aligned}
U(s) = \mathcal{L} \{u(t)\} &= \int_{0}^{\infty} u(t) e^{-st} dt = -\frac{1}{s} e^{-st} dt \\
U(s) &= -\frac{1}{s}(0-1) = \frac{1}{s}
\end{aligned} U ( s ) = L { u ( t )} U ( s ) = ∫ 0 ∞ u ( t ) e − s t d t = − s 1 e − s t d t = − s 1 ( 0 − 1 ) = s 1
L − 1 { F ( s ) } = 1 2 π j lim ω → ∞ ∫ σ − j ω σ + j ω F ( s ) e s t d s \mathcal{L}^{-1} \{ F(s) \} = \frac{1}{2\pi j} \lim_{\omega \to \infty} \int_{\sigma-j\omega}^{\sigma+j\omega} F(s) e^{st} \, ds L − 1 { F ( s )} = 2 πj 1 ω → ∞ lim ∫ σ − jω σ + jω F ( s ) e s t d s
Properties
f ( 0 − ) : initial condition just before 0 Linearity: L { k 1 f 1 ( t ) ± k 2 f 2 ( t ) } = k 1 F 1 ( s ) ± k 2 F 2 ( s ) Differentiation: L { d f ( t ) d t } = s F ( s ) − f ( 0 − ) L { d 2 f ( t ) d t 2 } = s 2 F ( s ) − s f ( 0 − ) − f ′ ( 0 − ) Frequency Shifting: L { e − a t f ( t ) } = F ( s + a ) \begin{aligned}
& f(0-)\text{: initial condition just before 0} \\[12pt]
& \textbf{Linearity:} \quad \mathcal{L}\{k_1 f_1(t) \pm k_2 f_2(t)\} = k_1 F_1(s) \pm k_2 F_2(s) \\[12pt]
& \textbf{Differentiation:} \\
& \quad \mathcal{L}\left\{\frac{df(t)}{dt}\right\} = sF(s) - f(0^-) \\
& \quad \mathcal{L}\left\{\frac{d^2f(t)}{dt^2}\right\} = s^2 F(s) - sf(0^-) - f'(0^-) \\[12pt]
& \textbf{Frequency Shifting:} \quad \mathcal{L}\{e^{-at}f(t)\} = F(s + a) \\
\end{aligned} f ( 0 − ) : initial condition just before 0 Linearity: L { k 1 f 1 ( t ) ± k 2 f 2 ( t )} = k 1 F 1 ( s ) ± k 2 F 2 ( s ) Differentiation: L { d t df ( t ) } = s F ( s ) − f ( 0 − ) L { d t 2 d 2 f ( t ) } = s 2 F ( s ) − s f ( 0 − ) − f ′ ( 0 − ) Frequency Shifting: L { e − a t f ( t )} = F ( s + a )
Transfer function
n t h n^{th} n t h order linear, time-invariant (LTI) differential equation:
a n d n c ( t ) d t n + a n − 1 d n − 1 c ( t ) d t n − 1 + ⋯ + a 0 c ( t ) = b m d m r ( t ) d t m + b m − 1 d m − 1 r ( t ) d t m − 1 + ⋯ + b 0 r ( t ) a_n \frac{d^n c(t)}{dt^n} + a_{n-1} \frac{d^{n-1} c(t)}{dt^{n-1}} + \cdots + a_0 c(t) = b_m \frac{d^m r(t)}{dt^m} + b_{m-1} \frac{d^{m-1} r(t)}{dt^{m-1}} + \cdots + b_0 r(t) a n d t n d n c ( t ) + a n − 1 d t n − 1 d n − 1 c ( t ) + ⋯ + a 0 c ( t ) = b m d t m d m r ( t ) + b m − 1 d t m − 1 d m − 1 r ( t ) + ⋯ + b 0 r ( t )
takes Laplace transform from both side
a n s n C ( s ) + a n − 1 s n − 1 C ( s ) + ⋯ + a 0 C ( s ) and init terms for c ( t ) = b m s m R ( s ) + b m − 1 s m − 1 R ( s ) + ⋯ + b 0 R ( s ) and init terms for r ( t ) \begin{aligned}
& a_n s^n C(s) + a_{n-1} s^{n-1} C(s) + \cdots + a_0 C(s) \text{ and init terms for } c(t) \\
& = b_m s^m R(s) + b_{m-1} s^{m-1} R(s) + \cdots + b_0 R(s) \text{ and init terms for } r(t) \\
\end{aligned} a n s n C ( s ) + a n − 1 s n − 1 C ( s ) + ⋯ + a 0 C ( s ) and init terms for c ( t ) = b m s m R ( s ) + b m − 1 s m − 1 R ( s ) + ⋯ + b 0 R ( s ) and init terms for r ( t )
assume initial conditions are zero
( a n s n + a n − 1 s n − 1 + ⋯ + a 0 ) C ( s ) = ( b m s m + b m − 1 s m − 1 + ⋯ + b 0 ) R ( s ) C ( s ) R ( s ) = G ( s ) = b m s m + b m − 1 s m − 1 + ⋯ + b 0 a n s n + a n − 1 s n − 1 + ⋯ + a 0 \begin{aligned}
(a_n s^n + a_{n-1} s^{n-1} + \cdots + a_0)C(s) &= (b_m s^m + b_{m-1} s^{m-1} + \cdots + b_0)R(s) \\[8pt]
\frac{C(s)}{R(s)} &= G(s) = \frac{b_m s^m + b_{m-1} s^{m-1} + \cdots + b_0}{a_n s^n + a_{n-1} s^{n-1} + \cdots + a_0}
\end{aligned} ( a n s n + a n − 1 s n − 1 + ⋯ + a 0 ) C ( s ) R ( s ) C ( s ) = ( b m s m + b m − 1 s m − 1 + ⋯ + b 0 ) R ( s ) = G ( s ) = a n s n + a n − 1 s n − 1 + ⋯ + a 0 b m s m + b m − 1 s m − 1 + ⋯ + b 0
G ( s ) = C ( s ) R ( s ) G(s)=\frac{C(s)}{R(s)} G ( s ) = R ( s ) C ( s )
Q: G ( s ) = 1 S + 2 G(s) = \frac{1}{S+2} G ( s ) = S + 2 1 . Input: u ( t ) u(t) u ( t ) . What is y ( t ) y(t) y ( t ) ?
Y ( s ) = G ( s ) ⋅ u ( s ) → Y ( s ) = 1 s ( s + 2 ) = A s + B s + 2 = 1 2 ⋅ s − 1 2 ⋅ ( s + 2 ) y ( t ) = − 1 2 ( 1 − e − 2 t ) u ( t ) \begin{aligned}
Y(s) &= G(s)\cdot u(s) \rightarrow Y(s)=\frac{1}{s(s+2)} = \frac{A}{s} + \frac{B}{s+2} = \frac{1}{2\cdot{s}} - \frac{1}{2\cdot{(s+2)}} \\
y(t) &= -\frac{1}{2}(1-e^{-2t})u(t)
\end{aligned} Y ( s ) y ( t ) = G ( s ) ⋅ u ( s ) → Y ( s ) = s ( s + 2 ) 1 = s A + s + 2 B = 2 ⋅ s 1 − 2 ⋅ ( s + 2 ) 1 = − 2 1 ( 1 − e − 2 t ) u ( t )
Partial fraction expansion
F ( s ) = N ( s ) D ( s ) N ( s ) : m t h order polynomial in s D ( s ) : n t h order polynomial in s \begin{aligned}
F(s) &= \frac{N(s)}{D(s)} \\[8pt]
N(s) &: m^{th} \text{ order polynomial in } s \\
D(s) &: n^{th} \text{ order polynomial in } s \\
\end{aligned} F ( s ) N ( s ) D ( s ) = D ( s ) N ( s ) : m t h order polynomial in s : n t h order polynomial in s
Decomposition of N ( s ) D ( s ) \frac{N(s)}{D(s)} D ( s ) N ( s )
Divide if improper : N ( s ) D ( s ) \frac{N(s)}{D(s)} D ( s ) N ( s ) such that degree of N ( s ) ≤ degree of D ( s ) \text{degree of }N(s) \leq \text{degree of } D(s) degree of N ( s ) ≤ degree of D ( s ) such that N ( s ) D ( s ) = a polynomial + N 1 ( s ) D ( s ) \frac{N(s)}{D(s)} = \text{a polynomial } + \frac{N_1(s)}{D(s)} D ( s ) N ( s ) = a polynomial + D ( s ) N 1 ( s )
Factor Denominator : into factor form
( p s + q ) m and ( a s 2 + b s + c ) n (ps+q)^m \text{ and } (as^2+bs+c)^n ( p s + q ) m and ( a s 2 + b s + c ) n
Linear Factors : ( p s + q ) m (ps+q)^m ( p s + q ) m such that:
∑ j = 1 m A j ( p s + q ) j \sum_{j=1}^{m}\frac{A_j}{(ps+q)^j} j = 1 ∑ m ( p s + q ) j A j
Quadratic Factors : ( a s 2 + b s + c ) n (as^2+bs+c)^n ( a s 2 + b s + c ) n such that
∑ j = 1 n B j s + C j ( a s 2 + b s + c ) j \sum_{j=1}^{n}{\frac{B_j s+C_j}{(as^2+bs+c)^j}} j = 1 ∑ n ( a s 2 + b s + c ) j B j s + C j
Determine Unknown
Stability analysis using Root of D ( s ) D(s) D ( s )
roots of D ( s ) D(s) D ( s ) as poles
G ( s ) = N ( s ) D ( s ) = N ( s ) ∏ j = 1 n ( s + p j ) = ∑ j = 1 n A j s + p j G(s) = \frac{N(s)}{D(s)} = \frac{N(s)}{\prod_{j=1}^{n}(s+p_j)} = \sum_{j=1}^{n}{\frac{A_j}{s+p_j}} G ( s ) = D ( s ) N ( s ) = ∏ j = 1 n ( s + p j ) N ( s ) = j = 1 ∑ n s + p j A j
p i p_i p i can be imaginary
Solving for g ( t ) g(t) g ( t ) gives
g ( t ) = ∑ j = 1 n L − 1 { A j ( s + p j ) } = ∑ j = 1 n A j e − p j t g(t) = \sum_{j=1}^{n}{\mathcal{L}^{-1}\{\frac{A_j}{(s+p_j)}\}} = \sum_{j=1}^{n}{A_je^{-p_jt}} g ( t ) = j = 1 ∑ n L − 1 { ( s + p j ) A j } = j = 1 ∑ n A j e − p j t
stability analysis
If σ i > 0 \sigma_i > 0 σ i > 0 then pole is in the left side of imaginary plane, and system is stable
Complex root
For poles at s = σ i ± j ω s=\sigma_i \pm j\omega s = σ i ± jω we get
α + j β s + σ i + j ω i + α − j β s + σ i − j ω i \frac{\alpha + j\beta}{s + \sigma_i + j\omega_i} + \frac{\alpha - j\beta}{s + \sigma_i - j\omega_i} s + σ i + j ω i α + j β + s + σ i − j ω i α − j β
Wants to be on LHP for time-function associated with s s s plane to be stable
Impedance of Inductor
Z ( s ) = V ( s ) I ( s ) = L s Z(s) = \frac{V(s)}{I(s)} = Ls Z ( s ) = I ( s ) V ( s ) = L s
since the voltage-current relation for an inductor is v ( t ) = L d i ( t ) d t v(t) = L\frac{di(t)}{dt} v ( t ) = L d t d i ( t )
Impedance of Capacitor
Z ( s ) = V ( s ) I ( s ) = 1 C s Z(s) = \frac{V(s)}{I(s)} = \frac{1}{Cs} Z ( s ) = I ( s ) V ( s ) = C s 1
since the voltage-current relation for a capacitor is v ( t ) = 1 C ∫ 0 t i ( τ ) d τ v(t) = \frac{1}{C} \int_0^{t}{i(\tau) d\tau} v ( t ) = C 1 ∫ 0 t i ( τ ) d τ