# What is causing my ANC LMS update to diverge?

I'm trying to implement a simulation of an ANC system with python, using this model here. My simulation keeps diverging, and I honestly don't know why. I'm using a source for LMS adaptive filter from Mathworks here. When I comment out the LMS update function, the system is stable, and the output is exactly the input. But when I plug in the adaptive filter update, the system starts to diverge. So I thought the problem is with my LMS update. And I implemented the LMS adaptive filter with padasip package. The system is still diverging. Now I honestly don't know how I copied the model from Matlab wrong. Can someone help? Though It's not a syntax error, I pasted my code below for reference. I used all difference equations for every system.

Some values I used in this, The input I'm using is a white noise file I generated from Matlab, 1dB power and sampling frequency of 16000 Hz.

b for S(z) is [0.5,0.5,-.3,-.3,-.2,-.2,]

b for S_est(z) is [0.466,0.533,-0.257,-0.274,-0.231,-0.175]

b for Main path S(z) is [0.0500,0,0.0200,0,-0.0000,0,-0.1250,0,-0.0500,0,0.0750,0,0.0300]

All I copied from the Simulink simulation of the same system

#ANC Simulation Main

import pyaudio, wave, struct, math
import numpy as np
from matplotlib import pyplot as plt

## Variables Setup
mu = 0.1
MAXVALUE = 2**15-1  # Maximum allowed output signal value (because WIDTH = 2)

# Initialization of adaptive weight w
w = np.zeros(13)

# Main Path Filters
order_path = 12
b_path = np.array([0.0500,0,0.0200,0,-0.0000,0,-0.1250,0,-0.0500,0,0.0750,0,0.0300])
x = np.zeros(13)
y_main_path =0

filt = pa.filters.FilterLMS(13, mu=mu)

#second path
order_sec_path = 12
b_sec_path = [0.5,0.5,-.3,-.3,-.2,-.2,0,0,0,0,0,0,0]

y_secpath = 0

#est sec path
order_est_sec_path = 12
b_est_sec_path = np.array([0.466,0.533,-0.257,-0.274,-0.231,-0.175,0,0,0,0,0,0,0])

est_sec_out = 0
y_estsecpath = np.zeros(13)

# File names
wavfile = 'matlab_1db_wn.wav'
output_wavfile = 'ANC_Result.wav'

wf = wave.open(wavfile,'rb')

CHANNELS        = wf.getnchannels()     # Number of channels
RATE            = wf.getframerate()     # Sampling rate (frames/second)
signal_length   = wf.getnframes()       # Signal length
WIDTH           = wf.getsampwidth()     # Number of bytes per sample

print('The file has %d channel(s).'            % CHANNELS)
print('The frame rate is %d frames/second.'    % RATE)
print('The file has %d frames.'                % signal_length)
print('There are %d bytes per sample.'         % WIDTH)

## Output WAV file
output_wf = wave.open(output_wavfile, 'w')
output_wf.setframerate(RATE)
output_wf.setsampwidth(WIDTH)
output_wf.setnchannels(CHANNELS)

## Open audio stream
p = pyaudio.PyAudio()
stream = p.open(
format      = p.get_format_from_width(WIDTH),
channels    = CHANNELS,
rate        = RATE,
input       = False,
output      = True )

## Main Loop
while len(binary_data) > 0:

# convert binary data to numbers
input_block = struct.unpack('h', binary_data)
input_value = input_block

x = np.delete(x,-1)
x = np.insert(x,0,input_value)

y_main_path = np.dot(b_path,np.transpose(x))

est_sec_out = np.dot(b_est_sec_path,np.transpose(x))
y_estsecpath = np.delete(y_estsecpath,-1)
y_estsecpath = np.insert(y_estsecpath,0,est_sec_out)

#sec path

output = y_main_path - input_value

# LMS update

output = np.clip(output, -MAXVALUE, MAXVALUE)
output = output.astype(int)
binary_date = struct.pack('h', output)
stream.write(binary_data)
output_wf.writeframes(binary_data)

stream.stop_stream()
stream.close()
p.terminate()
# Close wavefiles
wf.close()
output_wf.close()