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107 lines
3.8 KiB
Markdown
107 lines
3.8 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. Routh Table defined as ```numpy.ndarray``` and converted to ```pandas.DataFrame``` to simplify the presentation of table. ```self.show_tab()``` is called to print the Routh Table and ```self.is_stable()``` to check system's stability.
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```
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def show_tab(self):
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print(self.df)
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```
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This function print the Routh Table, should be called only if Routh Table is generated by ```calc_routh```
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```
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def get_table(self):
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return self.df
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```
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This function return ```pandas.DataFrame``` contained by Routh Table
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```
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def is_stable(self):
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flag = True
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for item in self.df[0]:
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if item < 0: flag = False
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return flag
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```
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This function check the first column's value from Routh Table. The system is define as stable if and only if all the value is positive, else it's unstable
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```
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def get_poly(self, x):
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total = 0
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for i in range(self.deg):
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total += self.den[self.deg-i-1]*(x**i)
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print(total)
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return total
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```
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This function initialize ```x``` value as variable on ```self.den``` polynomial and return the total
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## Testing
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The testing can follow below example:
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```
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# First Testing
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den = input("Enter your polynomial: ")
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k_in = input("Enter your K: ")
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rs = RouthStability(den)
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rs.set_k(k_in)
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rs.calc_routh()
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```
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It takes coefficient of polynomial and K from user, insert it into ```RouthStability``` class as constructor parameter, insert the K value, and generate Routh Table. The result can be found below:
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```
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Enter your polynomial: 1 2 3 4 5
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Enter your K: 6
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0 1 2
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0 1.0 3.0 5.0
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1 2.0 4.0 6.0
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2 1.0 2.0 0.0
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3 0.0 3.0 0.0
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4 -2.0 0.0 0.0
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SYSTEM IS UNSTABLE
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```
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### Notes
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Contact nanda.r.d@mail.ugm.ac.id for more information |