System Dynamics

Problems

Problem 11.1 (SCALLYWAG)

Use a computer to solve this problem. Consider the transfer function \[\begin{aligned} H(s) &= \frac{10 (s + 3)} {(s+2) (s^2 + 8 s + 41)}. \end{aligned}\]

  1. What are poles and zeros of \(H\)?

  2. Comment on the stability of the system described by \(H\) (justify your comment).

  3. Construct a pole-zero plot.

  4. Use a function like the Python control package function step_response() to simulate the unit step response of the system and plot it for \(t\in [0,3]\) seconds.

Problem 11.2 (SWASHBUCKLING)

Consider a system with linear state-space model matrices $$\begin{align} A &= \begin{bmatrix} -1 & 4 \\ 0 & -3 \end{bmatrix} & B &= \begin{bmatrix} 1 \\ -1 \end{bmatrix} \\ C&= \begin{bmatrix} 1 & 0 \end{bmatrix} & D &= \begin{bmatrix} 0 \end{bmatrix}. \end{align}$$

  1. Derive the transfer function \(H(s)\) for the system. Express it as a single ratio in \(s\).

  2. What are the poles and zeros?

  3. Compare the poles to the eigenvalues of \(A\).

  4. Draw or sketch a pole-zero plot.

  5. With reference to the pole-zero plot, comment on the stability and transient free response characteristics of the system.

  6. Use the inverse Laplace transform \(\mathcal{L}^{-1}\) to find the system’s forced response \(y(t)\) to step input \(u(t) = 9\,u_s(t)\).

Problem 11.3 (BORIS)

Consider a mass-spring-damper system with mass \(m\), spring constant \(k\), and damping coefficient \(B\) with the I/O ODE \[\begin{aligned} \ddot{y} + \frac{B} {m} \dot{y} + \frac{k} {m} y &= \frac{1} {m} u \end{aligned}\] for input force \(u(t) = F_S(t)\) and output position \(y(t) = x_m(t)\).

  1. Find the corresponding transfer function \(H(s) = Y(s)/U(s)\).

  2. Find the natural frequency and damping ratio in terms of system parameters \(m\), \(k\), and \(B\).

  3. What are poles and zeros of \(H\) in terms of system parameters \(m\), \(k\), and \(B\)?

  4. For system parameters \(m = 10\) kg, \(k = 1\cdot10^5\) N/m, and \(B = 500\) N\(\cdot\)s/m, construct a pole-zero plot.

  5. Comment on the stability of the system described by \(H\). Are there any values of system parameters \(m\), \(k\), and \(B\) for which the system is marginally stable or unstable?

  6. For system parameters \(m = 10\) kg, \(k = 1\cdot10^5\) N/m, and \(B = 500\) N\(\cdot\)s/m, use a function like the Python control package function step_response to simulate the unit step response of the system and plot it for \(t\in [0,0.3]\) s.

Problem 11.4 (RATTLESNAKE)

Consider the I/O ODE \[\begin{aligned} \dddot{y} + 6\ddot{y} + 11\dot{y} + 6y &= 2\dot{u} + 3u. \end{aligned}\]

  1. Find the transfer function \(H(s) = Y(s)/U(s)\).

  2. What are the degrees of the numerator and denominator polynomials?

  3. Find the DC gain \(H(0)\).

  4. Find the poles and zeros of \(H\).

  5. Comment on the stability of the system.

1. Taking the Laplace transform of the I/O ODE with zero initial conditions, \[\begin{aligned} (s^3 + 6s^2 + 11s + 6) Y(s) &= (2s + 3) U(s). \end{aligned}\] Therefore, \[\begin{aligned} H(s) = \frac{Y(s)}{U(s)} = \frac{2s + 3}{s^3 + 6s^2 + 11s + 6}. \end{aligned}\]

2. The numerator has degree 1 and the denominator has degree 3.

3. The DC gain is \[\begin{aligned} H(0) = \frac{3}{6} = \frac{1}{2}. \end{aligned}\]

4. The zero is found from \(2s + 3 = 0\), giving \(s = -3/2\). The denominator factors as \((s+1)(s+2)(s+3) = s^3 + 6s^2 + 11s + 6\), so the poles are at \(s = -1, -2, -3\).

5. All poles have negative real parts (\(-1\), \(-2\), and \(-3\)), so the system is asymptotically stable.

Optional: Python verification

Problem 11.5 (MARAUDER)

Consider the transfer function \[\begin{aligned} H(s) &= \frac{5s + 2}{s^2 + 4s + 13}. \end{aligned}\]

  1. Write the I/O ODE corresponding to \(H(s)\).

  2. Identify the natural frequency \(\omega_n\) and damping ratio \(\zeta\) from the denominator.

  3. Classify the system as underdamped, overdamped, or critically damped.

  4. Find the poles and zeros. Express the poles in the form \(\sigma \pm j\omega_d\).

  5. Sketch a pole-zero plot. On the plot, indicate \(\omega_n\) (as the distance from the origin to a pole) and \(\zeta\) (via the angle \(\cos^{-1}(\zeta)\) from the negative real axis to the line from the origin to a pole).

1. From \(H(s) = \frac{Y(s)}{U(s)} = \frac{5s + 2}{s^2 + 4s + 13}\), cross-multiplying gives \[\begin{aligned} (s^2 + 4s + 13) Y = (5s + 2) U. \end{aligned}\] Taking the inverse Laplace transform: \[\begin{aligned} \ddot{y} + 4\dot{y} + 13 y = 5\dot{u} + 2u. \end{aligned}\]

2. The standard second-order denominator form is \(s^2 + 2\zeta\omega_n s + \omega_n^2\). Comparing with \(s^2 + 4s + 13\): \[\begin{aligned} \omega_n^2 &= 13 \implies \omega_n = \sqrt{13} \approx 3.61 \text{ rad/s}, \\ 2\zeta\omega_n &= 4 \implies \zeta = \frac{2}{\sqrt{13}} \approx 0.555. \end{aligned}\]

3. Since \(0 < \zeta \approx 0.555 < 1\), the system is underdamped.

4. The zero is at \(s = -2/5\) (from \(5s + 2 = 0\)). The poles are the roots of \(s^2 + 4s + 13 = 0\): \[\begin{aligned} s = \frac{-4 \pm \sqrt{16 - 52}}{2} = \frac{-4 \pm \sqrt{-36}}{2} = -2 \pm 3j. \end{aligned}\] So \(\sigma = -2\) and \(\omega_d = 3\) rad/s.

5. The pole-zero plot has poles (×) at \(-2 \pm 3j\) and a zero (○) at \(-2/5\) on the real axis. The distance from the origin to either pole is \(\omega_n = \sqrt{(-2)^2 + 3^2} = \sqrt{13}\). The angle from the negative real axis to the line from the origin to the upper pole is \(\cos^{-1}(\zeta) = \cos^{-1}(2/\sqrt{13}) \approx 56.3°\).

Optional: Python verification

Problem 11.6 (GALLEON)

Consider a system with linear state-space model matrices $$\begin{align} A &= \begin{bmatrix} 0 & 1 \\ -5 & -4 \end{bmatrix} & B &= \begin{bmatrix} 0 \\ 1 \end{bmatrix} \\ C &= \begin{bmatrix} 3 & 0 \end{bmatrix} & D &= \begin{bmatrix} 0 \end{bmatrix}. \end{align}$$

  1. Compute the transfer function \(H(s) = C(sI - A)^{-1}B + D\) by hand. Show your work.

  2. Find the poles and zeros of \(H(s)\).

  3. Compute the eigenvalues of \(A\) and verify that they equal the poles.

  4. Comment on the stability of the system.

1. We compute \(H(s) = C(sI - A)^{-1}B + D\). First, \[\begin{aligned} sI - A = \begin{bmatrix} s & -1 \\ 5 & s+4 \end{bmatrix}. \end{aligned}\] The determinant is \(\det(sI - A) = s(s+4) + 5 = s^2 + 4s + 5\). The inverse is \[\begin{aligned} (sI - A)^{-1} = \frac{1}{s^2 + 4s + 5} \begin{bmatrix} s+4 & 1 \\ -5 & s \end{bmatrix}. \end{aligned}\] Then \[\begin{aligned} (sI - A)^{-1} B = \frac{1}{s^2 + 4s + 5} \begin{bmatrix} s+4 & 1 \\ -5 & s \end{bmatrix} \begin{bmatrix} 0 \\ 1 \end{bmatrix} = \frac{1}{s^2 + 4s + 5} \begin{bmatrix} 1 \\ s \end{bmatrix}. \end{aligned}\] So \[\begin{aligned} H(s) = C(sI - A)^{-1}B + D = \begin{bmatrix} 3 & 0 \end{bmatrix} \frac{1}{s^2 + 4s + 5} \begin{bmatrix} 1 \\ s \end{bmatrix} + 0 = \frac{3}{s^2 + 4s + 5}. \end{aligned}\]

2. There are no finite zeros (the numerator is the constant 3). The poles are the roots of \(s^2 + 4s + 5 = 0\): \[\begin{aligned} s = \frac{-4 \pm \sqrt{16 - 20}}{2} = -2 \pm j. \end{aligned}\]

3. The characteristic polynomial of \(A\) is \(\det(\lambda I - A) = \lambda^2 + 4\lambda + 5\), giving eigenvalues \(\lambda = -2 \pm j\). These match the poles.

4. Both poles have real part \(-2 < 0\), so the system is asymptotically stable.

Optional: Python verification

Problem 11.7 (CUTLASS)

Consider the following three transfer functions: $$\begin{align} H_1(s) &= \frac{2}{s^2 + 3s + 2} & H_2(s) &= \frac{s + 1}{s^2 + 4} & H_3(s) &= \frac{1}{s^2 - s - 6}. \end{align}$$

  1. Find the poles of each transfer function.

  2. Sketch a pole-zero plot for each.

  3. Classify each system as asymptotically stable, marginally stable, or unstable. Justify each classification.

  4. For the stable system(s), describe the qualitative nature of the free response (e.g., oscillatory, exponential decay, or a combination) based on whether the poles are real or complex.

1. \(H_1(s) = \frac{2}{s^2 + 3s + 2}\): The denominator factors as \((s+1)(s+2)\). Poles: \(s = -1, -2\). No finite zeros.

\(H_2(s) = \frac{s+1}{s^2 + 4}\): The denominator gives \(s^2 = -4\), so \(s = \pm 2j\). Poles: \(s = \pm 2j\). Zero: \(s = -1\).

\(H_3(s) = \frac{1}{s^2 - s - 6}\): The denominator factors as \((s-3)(s+2)\). Poles: \(s = 3, -2\). No finite zeros.

2.

  • \(H_1\): two real poles at \(-1\) and \(-2\) on the negative real axis; no zeros.
  • \(H_2\): two purely imaginary poles at \(\pm 2j\) on the imaginary axis; one real zero at \(-1\).
  • \(H_3\): two real poles at \(-2\) and \(3\) (one in each half-plane); no zeros.

3.

  • \(H_1\): Asymptotically stable. Both poles (\(s = -1, -2\)) have strictly negative real parts.
  • \(H_2\): Marginally stable. The poles (\(s = \pm 2j\)) lie on the imaginary axis with \(\operatorname{Re}(s) = 0\).
  • \(H_3\): Unstable. The pole at \(s = 3\) has a positive real part.

4. \(H_1\) is the only asymptotically stable system. Its poles are both real and negative, so the free response is a sum of two decaying exponentials \(c_1 e^{-t} + c_2 e^{-2t}\) with no oscillation.

Optional: Python verification

Problem 11.8 (BRIGANTINE)

Consider the transfer functions $$\begin{align} G(s) &= \frac{1}{s + 1} & H(s) &= \frac{s + 3}{s + 5}. \end{align}$$

  1. Compute the series (cascade) connection \(G(s) H(s)\). Express the result as a single ratio of polynomials.

  2. Compute the parallel connection \(G(s) + H(s)\). Express the result as a single ratio of polynomials.

  3. Compute the negative unity feedback connection \(\frac{G(s)}{1 + G(s)H(s)}\). Express the result as a single ratio of polynomials.

  4. Find the poles and zeros of each result from parts (a)–(c). Comment on any differences in stability.

1. Series connection: \[\begin{aligned} G(s)H(s) = \frac{1}{s+1} \cdot \frac{s+3}{s+5} = \frac{s+3}{(s+1)(s+5)} = \frac{s+3}{s^2 + 6s + 5}. \end{aligned}\]

2. Parallel connection: \[\begin{aligned} G(s) + H(s) &= \frac{1}{s+1} + \frac{s+3}{s+5} = \frac{(s+5) + (s+3)(s+1)}{(s+1)(s+5)} \\ &= \frac{s + 5 + s^2 + 4s + 3}{s^2 + 6s + 5} = \frac{s^2 + 5s + 8}{s^2 + 6s + 5}. \end{aligned}\]

3. Negative unity feedback: \[\begin{aligned} \frac{G}{1 + GH} &= \frac{\frac{1}{s+1}}{1 + \frac{1}{s+1}\cdot\frac{s+3}{s+5}} = \frac{\frac{1}{s+1}}{\frac{(s+1)(s+5) + (s+3)}{(s+1)(s+5)}} = \frac{s+5}{(s+1)(s+5) + (s+3)} \\ &= \frac{s+5}{s^2 + 7s + 8}. \end{aligned}\]

4. Poles and zeros:

  • Series: poles at \(s = -1, -5\); zero at \(s = -3\). All poles in LHP \(\Rightarrow\) stable.
  • Parallel: poles at \(s = -1, -5\); zeros at \(s = \frac{-5 \pm j\sqrt{7}}{2} \approx -2.5 \pm 1.32j\). Stable.
  • Feedback: zero at \(s = -5\); poles at \(s = \frac{-7 \pm \sqrt{17}}{2} \approx -1.44, -5.56\). Stable.

All three connections are asymptotically stable. The feedback connection shifts the pole locations relative to the open-loop poles.

Optional: Python verification

Problem 11.9 (DOUBLOON)

Consider the transfer function \[\begin{aligned} H(s) &= \frac{3}{s + 2} \end{aligned}\] with input \(u(t) = 5\,u_s(t)\), where \(u_s(t)\) is the unit step function.

  1. Find the Laplace transform \(U(s)\) of the input.

  2. Use the transfer function to find the output in the Laplace domain: \(Y(s) = H(s) U(s)\).

  3. Perform partial fraction expansion on \(Y(s)\). Hint: The partial fraction expansion of \(\frac{K}{s(s+a)}\) takes the form \(\frac{A}{s} + \frac{B}{s+a}\). To find the coefficients, multiply both sides by the denominator \(s(s+a)\) and evaluate at convenient values of \(s\). For instance, setting \(s = 0\) isolates \(A\) and setting \(s = -a\) isolates \(B\).

  4. Take the inverse Laplace transform to find \(y(t)\) for \(t \ge 0\).

  5. What is the steady-state value \(\lim_{t\to\infty} y(t)\)? Verify that this is consistent with the DC gain \(H(0)\) and the input amplitude.

1. The Laplace transform of \(u(t) = 5\,u_s(t)\) is \(U(s) = \frac{5}{s}\).

2. The output in the Laplace domain is \[\begin{aligned} Y(s) = H(s) U(s) = \frac{3}{s+2} \cdot \frac{5}{s} = \frac{15}{s(s+2)}. \end{aligned}\]

3. Partial fraction expansion: we write \[\begin{aligned} \frac{15}{s(s+2)} = \frac{A}{s} + \frac{B}{s+2}. \end{aligned}\] Multiplying both sides by \(s(s+2)\): \[\begin{aligned} 15 = A(s+2) + Bs. \end{aligned}\] Setting \(s = 0\): \(15 = 2A\), so \(A = 15/2\). Setting \(s = -2\): \(15 = -2B\), so \(B = -15/2\). Therefore, \[\begin{aligned} Y(s) = \frac{15/2}{s} - \frac{15/2}{s+2}. \end{aligned}\]

4. Using the standard pairs \(\mathcal{L}^{-1}\{1/s\} = u_s(t)\) and \(\mathcal{L}^{-1}\{1/(s+a)\} = e^{-at} u_s(t)\): \[\begin{aligned} y(t) = \frac{15}{2}\left(1 - e^{-2t}\right), \quad t \ge 0. \end{aligned}\]

5. As \(t \to \infty\), \(e^{-2t} \to 0\), so \(\lim_{t\to\infty} y(t) = 15/2 = 7.5\). The DC gain is \(H(0) = 3/2\), and the input amplitude is \(5\), so \(H(0) \times 5 = (3/2)(5) = 15/2 = 7.5\). Consistent. \(\checkmark\)

Optional: Python verification

Problem 11.10 (COMPASS)

Use a computer to solve this problem. Consider the second-order transfer function \[\begin{aligned} H(s) &= \frac{\omega_n^2}{s^2 + 2\zeta\omega_n s + \omega_n^2} \end{aligned}\] with \(\omega_n = 10\) rad/s.

  1. Using Python, compute the poles for each of \(\zeta = 0.1\), \(0.5\), \(1.0\), and \(2.0\).

  2. Plot all four pairs of pole locations on a single pole-zero plot. Label or use a legend to distinguish the \(\zeta\) values.

  3. Simulate the unit step response for each \(\zeta\) value and plot them together for \(t \in [0, 2]\) s.

  4. Comment on the relationship between the pole locations and the step response character for each case.

Problem 11.11 (ANCHOR)

Use a computer to solve this problem. Consider a system with linear state-space model matrices $$\begin{align} A &= \begin{bmatrix} -1 & 0 & 0 \\ 0 & -2 & 0 \\ 0 & 0 & -3 \end{bmatrix} & B &= \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix} \\ C &= \begin{bmatrix} 1 & 1 & 1 \end{bmatrix} & D &= \begin{bmatrix} 0 \end{bmatrix}. \end{align}$$

  1. Define the state-space model using control.ss() and convert it to a transfer function using control.tf().

  2. Verify that the poles of the transfer function match the eigenvalues of \(A\) (e.g., using np.linalg.eig()).

  3. Generate a pole-zero plot and comment on stability.

  4. Simulate the unit step response for \(t \in [0, 8]\) s and plot the result.

Online Resources for Section 11.6

No online resources.