Added more noise simulation and a multi-simulate file that auto-runs multiple simulations with a desired noise level.

This commit is contained in:
2025-11-23 14:08:21 -06:00
parent 4435f55d1f
commit b721ae8fa3
9 changed files with 581 additions and 45 deletions

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@@ -6,44 +6,136 @@ Ported from quadParamsScript.m and constantsScript.m
import numpy as np
# Global parameter variations - initialized once per simulation run
_param_variations = None
def initialize_parameter_variations(noise_level=0.05, seed=None):
"""
Initialize mechanical and electrical parameter variations.
Call this once at the start of a simulation to set random variations.
Parameters
----------
noise_level : float, optional
Standard deviation of multiplicative noise (default: 0.05 = 5%)
seed : int, optional
Random seed for reproducibility
Returns
-------
dict
Dictionary with parameter variation factors
"""
global _param_variations
if seed is not None:
np.random.seed(seed)
# Generate multiplicative variation factors for each parameter
_param_variations = {
'mass': 1 + np.random.normal(0, noise_level),
'Jq_components': np.array([1 + np.random.normal(0, noise_level) for _ in range(3)]), # Individual noise for each inertia component
'frame_l': 1 + np.random.normal(0, noise_level * 0.5), # Smaller variation for dimensions
'frame_w': 1 + np.random.normal(0, noise_level * 0.5),
'yh': 1 + np.random.normal(0, noise_level * 0.5),
# Individual yoke variations (4 yokes)
'yoke_R': np.array([1 + np.random.normal(0, noise_level * 0.3) for _ in range(4)]),
'yoke_L': np.array([1 + np.random.normal(0, noise_level * 0.3) for _ in range(4)]),
# Position noise for yoke/rotor locations (4 locations, 3D)
'rotor_pos_noise': np.random.normal(0, noise_level * 0.2, (3, 4)),
# Position noise for sensor locations (4 sensors, 3D)
'sensor_pos_noise': np.random.normal(0, noise_level * 0.2, (3, 4))
}
return _param_variations.copy()
def get_parameter_variations():
"""
Get current parameter variations. If not initialized, use nominal (no variation).
Returns
-------
dict
Dictionary with parameter variation factors
"""
global _param_variations
if _param_variations is None:
# Use nominal values (no variation)
_param_variations = {
'mass': 1.0,
'Jq_components': np.ones(3),
'frame_l': 1.0,
'frame_w': 1.0,
'yh': 1.0,
'yoke_R': np.ones(4),
'yoke_L': np.ones(4),
'rotor_pos_noise': np.zeros((3, 4)),
'sensor_pos_noise': np.zeros((3, 4))
}
return _param_variations
def reset_parameter_variations():
"""Reset parameter variations to force reinitialization"""
global _param_variations
_param_variations = None
class QuadParams:
"""Quadrotor/maglev pod parameters"""
def __init__(self):
# Pod mechanical characteristics
frame_l = 0.61
frame_w = 0.149 # in meters
self.yh = 3 * 0.0254 # yoke height
# Get parameter variations
pv = get_parameter_variations()
# Pod mechanical characteristics (with variations)
frame_l = 0.61 * pv['frame_l']
frame_w = 0.149 * pv['frame_w']
self.yh = 3 * 0.0254 * pv['yh'] # yoke height
yh = self.yh
# Yoke/rotor locations (at corners)
self.rotor_loc = np.array([
# Store dimensions for reference
self.frame_l = frame_l
self.frame_w = frame_w
# Yoke/rotor locations (at corners) with position noise
nominal_rotor_loc = np.array([
[frame_l/2, frame_l/2, -frame_l/2, -frame_l/2],
[-frame_w/2, frame_w/2, frame_w/2, -frame_w/2],
[yh, yh, yh, yh]
])
self.rotor_loc = nominal_rotor_loc * (1 + pv['rotor_pos_noise'])
# Sensor locations (independent from yoke/rotor locations, at edge centers)
self.sensor_loc = np.array([
# Sensor locations (independent from yoke/rotor locations, at edge centers) with position noise
nominal_sensor_loc = np.array([
[frame_l/2, 0, -frame_l/2, 0],
[0, frame_w/2, 0, -frame_w/2],
[yh, yh, yh, yh]
])
self.sensor_loc = nominal_sensor_loc * (1 + pv['sensor_pos_noise'])
self.gap_sigma = 0.5e-3 # usually on micron scale
# Mass of the quad, in kg
self.m = 6
# Mass of the quad, in kg (with variation)
self.m = 6 * pv['mass']
# The quad's moment of inertia, expressed in the body frame, in kg-m^2
self.Jq = np.diag([0.017086, 0.125965, 0.131940])
# The quad's moment of inertia, expressed in the body frame, in kg-m^2 (with individual component variations)
nominal_Jq = np.diag([0.017086, 0.125965, 0.131940])
self.Jq = nominal_Jq * np.diag(pv['Jq_components']) # Apply different noise to each diagonal component
self.invJq = np.linalg.inv(self.Jq)
# Quad electrical characteristics
# Quad electrical characteristics (with variations)
maxcurrent = 30
self.yokeR = 2.2 # in ohms
self.yokeL = 5e-3 # in henries (2.5mH per yoke)
self.maxVoltage = maxcurrent * self.yokeR # max magnitude voltage supplied to each yoke
# Individual yoke resistances and inductances (4 yokes with individual variations)
self.yokeR_individual = 2.2 * pv['yoke_R'] # 4-element array
self.yokeL_individual = 5e-3 * pv['yoke_L'] # 4-element array
self.maxVoltage = maxcurrent * self.yokeR_individual # max magnitude voltage supplied to each yoke
class Constants: