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https://github.com/gabrielkheisa/control-system.git
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53 lines
2.2 KiB
Markdown
53 lines
2.2 KiB
Markdown
# routh_table
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This repo is belong to Control System class contains with Automated Routh Table Calculator based on Python. This code 100% original made by my hand :), please leave some notes if you're going to use it. Thanks!
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## Libraries
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Libraries that used in this program is ```numpy``` and ```pandas```. ```numpy``` works by define and perform array while ```pandas``` is the final form after ```numpy.array``` to simplify the presentation. They imported by write
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```
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import numpy as np
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import pandas as pd
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```
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## RouthStability Class
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This class contains lots of procedures to simplify our Routh Stability Table Generator process.
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```
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def __init__(self, den):
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self.den = np.array([float(item) for item in den.split()])
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self.deg = len(self.den)
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```
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The constructor ```__init__``` takes string of coefficiens from polynomial, extract the number, and load into class variable. It also define ```self.deg``` variable to save array's length, reducing number of calling ```len()``` function
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```
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def set_k(self, k):
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self.den = np.append(self.den, float(k))
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self.deg += 1
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```
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This function only takes one number from user and append it to ```self.den``` which defined as gain (constant). Also ```self.deg``` will increase by one
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```
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def calc_routh(self):
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height = (self.deg+1)//2
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arr = np.zeros((height + 2,height))
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for index in range(self.deg):
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if index % 2 == 0:
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arr[0][index//2] = self.den[index]
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else:
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arr[1][(index-1)//2] = self.den[index]
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for i in range(2, height+2):
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for j in range(height-1):
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arr[i][j] = (arr[i-1][0]*arr[i-2][j+1] - arr[i-2][0]*arr[i-1][j+1])//2
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arr[i][j] += 0
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self.df = pd.DataFrame(arr)
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self.show_tab()
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if self.is_stable() == True:
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print("SYSTEM IS STABLE")
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else:
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print("SYSTEM IS UNSTABLE")
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```
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```calc_routh(self)``` as the core process of this class contains initialization and process about Routh Stability Process. Firstly, it define an empty zero (basically it filled with zeros) and iteratively being inserted by ```self.den``` (refering to Routh Table principle). After that, each cell will be updated by calculating Routh Table formula
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```math
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arr_{i,j} = \frac{arr_{i-1][0]*arr[i-2][j+1] - arr[i-2][0]*arr[i-1][j+1]}{arr_{i-1][0]}
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```
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