Obsidian/Presentations/20251215-Emerson-Pres/bouncing_ball_hybrid.py
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A  Presentations/20251215-Emerson-Pres/bouncing_ball_hybrid.py

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Python

"""
Hybrid Dynamical System: Bouncing Ball in 1-D
This model demonstrates a hybrid system with:
- Flow State 1: Free fall (when ball center of mass is above radius r)
- Flow State 2: Spring-mass-damper (when ball is in contact with ground)
- Discrete transitions between these states
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import solve_ivp
class HybridBouncingBall:
def __init__(self, m=0.1, r=0.1, g=9.81, k=5000.0, c=10.0):
"""
Parameters:
-----------
m : float
Mass of the ball (kg)
r : float
Radius of the ball (m)
g : float
Gravitational acceleration (m/s^2)
k : float
Spring constant when in contact with ground (N/m)
c : float
Damping coefficient when in contact with ground (N·s/m)
"""
self.m = m
self.r = r
self.g = g
self.k = k
self.c = c
# For tracking state transitions
self.state_history = []
self.transition_times = []
def free_fall_dynamics(self, t, y):
"""
Flow dynamics for free fall state.
State: y = [position, velocity]
"""
pos, vel = y
dpos = vel
dvel = -self.g
return [dpos, dvel]
def spring_damper_dynamics(self, t, y):
"""
Flow dynamics for spring-mass-damper state.
State: y = [position, velocity]
When ball is compressed against ground:
F = -k*(r - pos) - c*vel - m*g
"""
pos, vel = y
dpos = vel
# Spring force kicks in when position < r
# Compression is (r - pos)
compression = self.r - pos
spring_force = self.k * compression
damping_force = self.c * vel
dvel = (spring_force - damping_force - self.m * self.g) / self.m
return [dpos, dvel]
def event_contact_ground(self, t, y):
"""Event: Ball contacts ground (transition to spring-damper)"""
pos, vel = y
return pos - self.r
def event_leave_ground(self, t, y):
"""Event: Ball leaves ground (transition to free fall)"""
pos, vel = y
# Leave ground when position > r AND velocity > 0
if pos > self.r and vel > 0:
return 0
return 1
# Make events terminal to stop integration
event_contact_ground.terminal = True
event_leave_ground.terminal = True
def simulate(self, y0, t_span, max_transitions=20):
"""
Simulate the hybrid system.
Parameters:
-----------
y0 : list
Initial state [position, velocity]
t_span : tuple
Time span (t_start, t_end)
max_transitions : int
Maximum number of state transitions to simulate
Returns:
--------
t_all : array
Time points
y_all : array
State trajectory
states : list
State labels ('free_fall' or 'spring_damper')
"""
t_all = []
y_all = []
states = []
current_state = "free_fall" if y0[0] > self.r else "spring_damper"
current_y = y0
current_t = t_span[0]
t_end = t_span[1]
transitions = 0
while current_t < t_end and transitions < max_transitions:
if current_state == "free_fall":
# Integrate free fall until contact with ground
sol = solve_ivp(
self.free_fall_dynamics,
[current_t, t_end],
current_y,
events=self.event_contact_ground,
dense_output=True,
max_step=0.01,
)
# Store results
t_all.append(sol.t)
y_all.append(sol.y.T)
states.extend(["free_fall"] * len(sol.t))
# Check if event occurred
if sol.t_events[0].size > 0:
# Transition to spring-damper
current_state = "spring_damper"
current_t = sol.t[-1]
current_y = sol.y[:, -1]
self.transition_times.append(current_t)
transitions += 1
else:
break
else: # spring_damper
# Integrate spring-damper until leaving ground
sol = solve_ivp(
self.spring_damper_dynamics,
[current_t, t_end],
current_y,
events=self.event_leave_ground,
dense_output=True,
max_step=0.01,
)
# Store results
t_all.append(sol.t)
y_all.append(sol.y.T)
states.extend(["spring_damper"] * len(sol.t))
# Check if event occurred
if sol.t_events[0].size > 0:
# Transition to free fall
current_state = "free_fall"
current_t = sol.t[-1]
current_y = sol.y[:, -1]
self.transition_times.append(current_t)
transitions += 1
else:
break
# Concatenate all results
t_all = np.concatenate(t_all)
y_all = np.vstack(y_all)
return t_all, y_all, states
def plot_simulation(t, y, states, ball, show_phase=True):
"""
Plot the simulation results.
Parameters:
-----------
t : array
Time points
y : array
State trajectory
states : list
State labels
ball : HybridBouncingBall
Ball object
show_phase : bool
Whether to show phase portrait
"""
# Convert states to numeric for coloring
state_numeric = np.array([1 if s == "free_fall" else 2 for s in states])
if show_phase:
fig, axes = plt.subplots(2, 1, figsize=(8, 10))
else:
fig, axes = plt.subplots(2, 1, figsize=(12, 8))
axes = axes.reshape(-1, 1)
# Plot 1: Position vs Time
ax1 = axes[0] if show_phase else axes[0]
scatter = ax1.scatter(t, y[:, 0], c=state_numeric, s=1, cmap="coolwarm", alpha=0.6)
ax1.axhline(
y=ball.r,
color="k",
linestyle="--",
label=f"Ground contact (h={ball.r}m)",
linewidth=1,
)
ax1.axhline(
y=0, color="gray", linestyle="-", label="Ground level", linewidth=1, alpha=0.5
)
# Mark transitions
for t_trans in ball.transition_times:
ax1.axvline(x=t_trans, color="green", linestyle=":", alpha=0.3, linewidth=1)
ax1.set_xlabel("Time (s)", fontsize=11)
ax1.set_ylabel("Position (m)", fontsize=11)
ax1.set_title("Ball Position vs Time", fontsize=12, fontweight="bold")
ax1.grid(True, alpha=0.3)
ax1.legend(fontsize=9)
if show_phase:
# Plot 2: Vector Field / Phase Portrait
ax2 = axes[1]
# Create vector field grid
pos_range = np.linspace(0, max(y[:, 0]) * 1.1, 15)
vel_range = np.linspace(min(y[:, 1]) * 1.1, max(y[:, 1]) * 1.1, 15)
Pos, Vel = np.meshgrid(pos_range, vel_range)
# Calculate vector field
dPos = np.zeros_like(Pos)
dVel = np.zeros_like(Vel)
for i in range(Pos.shape[0]):
for j in range(Pos.shape[1]):
pos_val = Pos[i, j]
vel_val = Vel[i, j]
# Determine which dynamics to use
if pos_val > ball.r:
# Free fall dynamics
dPos[i, j] = vel_val
dVel[i, j] = -ball.g
else:
# Spring-damper dynamics
dPos[i, j] = vel_val
compression = ball.r - pos_val
spring_force = ball.k * compression
damping_force = ball.c * vel_val
dVel[i, j] = (spring_force - damping_force - ball.m * ball.g) / ball.m
# Plot vector field with much smaller scale
ax2.quiver(Pos, Vel, dPos, dVel, alpha=0.3, color='gray', scale=300, width=0.003)
# Plot trajectory
scatter2 = ax2.scatter(
y[:, 0], y[:, 1], c=state_numeric, s=2, cmap="coolwarm", alpha=0.7
)
ax2.axvline(
x=ball.r, color="k", linestyle="--", label=f"Contact threshold", linewidth=1.5
)
ax2.axhline(y=0, color="gray", linestyle="-", linewidth=1, alpha=0.5)
ax2.set_xlabel("Position (m)", fontsize=11)
ax2.set_ylabel("Velocity (m/s)", fontsize=11)
ax2.set_title("Vector Field & Phase Portrait", fontsize=12, fontweight="bold")
ax2.grid(True, alpha=0.3)
ax2.legend(fontsize=9)
plt.tight_layout()
return fig
if __name__ == "__main__":
# Create ball with specific parameters
ball = HybridBouncingBall(
m=0.10, # 1 kg mass
r=0.1, # 10 cm radius
g=9.81, # Earth gravity
k=500.0, # Spring constant
c=0.89, # Damping coefficient
)
# Initial conditions: drop from 2 meters with zero velocity
y0 = [1.0, 0.0] # [position (m), velocity (m/s)]
# Simulate for 5 seconds
t_span = (0, 5.0)
print("Simulating hybrid bouncing ball system...")
print(f"Initial conditions: h0 = {y0[0]} m, v0 = {y0[1]} m/s")
print(
f"Ball parameters: m={ball.m} kg, r={ball.r} m, k={ball.k} N/m, c={ball.c} N·s/m"
)
print()
t, y, states = ball.simulate(y0, t_span, max_transitions=30)
print(f"Simulation complete!")
print(f"Total time simulated: {t[-1]:.3f} s")
print(f"Number of state transitions: {len(ball.transition_times)}")
print(f"Transition times: {[f'{tt:.3f}' for tt in ball.transition_times[:10]]}")
print()
# Count time in each state
free_fall_count = states.count("free_fall")
spring_damper_count = states.count("spring_damper")
total_points = len(states)
print(f"Time distribution:")
print(f" Free fall: {free_fall_count/total_points*100:.1f}%")
print(f" Spring-damper: {spring_damper_count/total_points*100:.1f}%")
# Plot results
fig = plot_simulation(t, y, states, ball, show_phase=True)
plt.savefig(
"/home/danesabo/Documents/Dane's Vault/Presentations/ERLM/bouncing_ball_hybrid.png",
dpi=300,
bbox_inches="tight",
)
print(f"\nPlot saved to: bouncing_ball_hybrid.png")
plt.show()