Difference between revisions of "Figure 5.7: Phase portrait and time domain simulation for a system with a single stable equilibrium point"
Jump to navigation
Jump to search
(3 intermediate revisions by the same user not shown) | |||
Line 7: | Line 7: | ||
}} | }} | ||
{| | {| | ||
− | |- | + | |- align=top |
| rowspan=3 | [[Image:figure-5.7-stable_eqpt-pp.png]] | | rowspan=3 | [[Image:figure-5.7-stable_eqpt-pp.png]] | ||
− | | <math> \begin{aligned} \dot x_1 &= x_2 \\ \dot x_2 &= -x_1 \end{aligned} </math> | + | | align=center | <math> \begin{aligned} \dot x_1 &= x_2 \\ \dot x_2 &= -2 x_1 \end{aligned} </math> |
− | |- | + | |- align=bottom |
| rowspan=2 | [[Image:figure-5.7-stable_eqpt-time.png]] | | rowspan=2 | [[Image:figure-5.7-stable_eqpt-time.png]] | ||
|- | |- | ||
|} | |} | ||
+ | '''Figure 5.7:''' Phase portrait and time domain simulation for a system with a single stable equilibrium point. The equilibrium point xe at the origin is stable since all trajectories that start near xe stay near xe. | ||
<nowiki> | <nowiki> | ||
− | + | # stable_eqpt.py - plots for stable equlibrium point | |
+ | # RMM, 6 Apr 2024 | ||
+ | import matplotlib.pyplot as plt | ||
+ | import numpy as np | ||
+ | from math import pi | ||
+ | import control as ct | ||
+ | import control.phaseplot as pp | ||
+ | import fbs # FBS plotting customizations | ||
− | + | m, b, k = 1, 0, 2 | |
+ | linsys = ct.ss([[0, 1], [-k/m, -b/m]], [[0], [1]], np.eye(2), 0) | ||
− | + | # Draw the phase portrait | |
+ | fbs.figure() | ||
+ | ct.phase_plane_plot(linsys, [-1, 1, -1, 1], 1, plot_streamlines=False) | ||
+ | pp.streamlines( | ||
+ | linsys, np.array([[0.2, 0], [0.4, 0], [0.6, 0], [0.8, 0], [1, 0]]), | ||
+ | 4.5, arrows=6) | ||
+ | plt.gca().set_aspect('equal') | ||
+ | plt.suptitle("") | ||
+ | |||
+ | # Add some level sets | ||
+ | theta = np.linspace(0, 2*pi) | ||
+ | plt.plot(0.2 * np.sin(theta), 0.2 * np.cos(theta), 'r--') | ||
+ | plt.plot(0.3 * np.sin(theta), 0.3 * np.cos(theta), 'r--') | ||
+ | |||
+ | fbs.savefig('figure-5.7-stable_eqpt-pp.png') | ||
+ | |||
+ | fbs.figure('321') | ||
+ | plt.axis([0, 10, -2.5, 2.5]) | ||
+ | timepts = np.linspace(0, 10) | ||
+ | response = ct.input_output_response(linsys, timepts, 0, [1, 0]) | ||
+ | plt.plot(response.time, response.outputs[0], 'b', label="$x_1$") | ||
+ | plt.plot(response.time, response.outputs[1], 'r--', label="$x_2$") | ||
+ | plt.xlabel("Time $t$") | ||
+ | plt.ylabel("$x_1, x_2$") | ||
+ | plt.legend(loc='upper right', ncols=2, frameon=False) | ||
+ | fbs.savefig('figure-5.7-stable_eqpt-time.png') | ||
</nowiki> | </nowiki> |
Latest revision as of 16:02, 7 April 2024
Chapter | Dynamic Behavior |
---|---|
Figure number | 5.7 |
Figure title | 5.7: Phase portrait and time domain simulation for a system with a single stable equilibrium point |
GitHub URL | https://github.com/murrayrm/fbs2e-python/blob/main/figure-5.7-stable-eqpt.py |
Requires | python-control |
Figure 5.7: Phase portrait and time domain simulation for a system with a single stable equilibrium point. The equilibrium point xe at the origin is stable since all trajectories that start near xe stay near xe.
# stable_eqpt.py - plots for stable equlibrium point # RMM, 6 Apr 2024 import matplotlib.pyplot as plt import numpy as np from math import pi import control as ct import control.phaseplot as pp import fbs # FBS plotting customizations m, b, k = 1, 0, 2 linsys = ct.ss([[0, 1], [-k/m, -b/m]], [[0], [1]], np.eye(2), 0) # Draw the phase portrait fbs.figure() ct.phase_plane_plot(linsys, [-1, 1, -1, 1], 1, plot_streamlines=False) pp.streamlines( linsys, np.array([[0.2, 0], [0.4, 0], [0.6, 0], [0.8, 0], [1, 0]]), 4.5, arrows=6) plt.gca().set_aspect('equal') plt.suptitle("") # Add some level sets theta = np.linspace(0, 2*pi) plt.plot(0.2 * np.sin(theta), 0.2 * np.cos(theta), 'r--') plt.plot(0.3 * np.sin(theta), 0.3 * np.cos(theta), 'r--') fbs.savefig('figure-5.7-stable_eqpt-pp.png') fbs.figure('321') plt.axis([0, 10, -2.5, 2.5]) timepts = np.linspace(0, 10) response = ct.input_output_response(linsys, timepts, 0, [1, 0]) plt.plot(response.time, response.outputs[0], 'b', label="$x_1$") plt.plot(response.time, response.outputs[1], 'r--', label="$x_2$") plt.xlabel("Time $t$") plt.ylabel("$x_1, x_2$") plt.legend(loc='upper right', ncols=2, frameon=False) fbs.savefig('figure-5.7-stable_eqpt-time.png')