diff --git a/442385_Nanda_Sisken_Assign_3.ipynb b/Assignment 3 - Routh Table/442385_Nanda_Sisken_Assign_3.ipynb
similarity index 100%
rename from 442385_Nanda_Sisken_Assign_3.ipynb
rename to Assignment 3 - Routh Table/442385_Nanda_Sisken_Assign_3.ipynb
diff --git a/Assignment 3 - Routh Table/README.md b/Assignment 3 - Routh Table/README.md
new file mode 100644
index 0000000..d70fe3a
--- /dev/null
+++ b/Assignment 3 - Routh Table/README.md	
@@ -0,0 +1,134 @@
+# routh_table
+This dir 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!
+
+## Libraries
+Libraries that used in this program is ```numpy``` and ```pandas```. ```numpy``` works to define and perform array while ```pandas``` is the final form after ```numpy.array``` to simplify the presentation. They imported by write..
+```
+import numpy as np
+import pandas as pd
+```
+
+## RouthStability Class
+This class contains lots of procedures to simplify our Routh Stability Table Generator process. 
+```
+def __init__(self, den):
+    self.den = np.array([float(item) for item in den.split()])
+    self.deg = len(self.den)
+```
+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 to calling ```len()``` function
+
+```
+def set_k(self, k):
+    self.den = np.append(self.den, float(k))
+    self.deg += 1
+```
+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
+
+```
+def calc_routh(self):
+    height = (self.deg+1)//2
+    arr = np.zeros((height + 2,height))
+    for index in range(self.deg):
+        if index % 2 == 0:
+        arr[0][index//2] = self.den[index]
+        else:
+        arr[1][(index-1)//2] = self.den[index]
+
+    for i in range(2, height+2):
+        for j in range(height-1):
+        arr[i][j] = (arr[i-1][0]*arr[i-2][j+1] - arr[i-2][0]*arr[i-1][j+1])/arr[i-1][0]
+        arr[i][j] += 0
+
+    self.df = pd.DataFrame(arr)
+    self.show_tab()
+    if self.is_stable() == True:
+        print("SYSTEM IS STABLE")
+    else:
+        print("SYSTEM IS UNSTABLE")
+```
+```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.
+
+```
+def show_tab(self):
+    print(self.df)
+```
+This function print the Routh Table, should be called only if Routh Table is generated by ```calc_routh```
+
+```
+def get_table(self):
+    return self.df
+```
+This function return ```pandas.DataFrame``` contained by Routh Table
+
+```
+def is_stable(self):
+    flag = True
+    for item in self.df[0]:
+        if item < 0: flag = False
+    return flag
+```
+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
+
+```
+def get_poly(self, x):
+    total = 0
+    for i in range(self.deg):
+        total += self.den[self.deg-i-1]*(x**i)
+        print(total)
+    return total
+```
+This function initialize ```x``` value as variable on ```self.den``` polynomial and return the total
+
+## Testing 1
+The testing can follow below example:
+```
+# First Testing
+den = input("Enter your polynomial: ")
+k_in = input("Enter your K: ")
+
+rs = RouthStability(den)
+rs.set_k(k_in)
+rs.calc_routh()
+```
+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:
+```
+Enter your polynomial: 1 3 5 7
+Enter your K: 9
+          0    1    2
+0  1.000000  5.0  9.0
+1  3.000000  7.0  0.0
+2  2.666667  9.0  0.0
+3 -3.125000  0.0  0.0
+4  9.000000 -0.0  0.0
+SYSTEM IS UNSTABLE
+```
+
+## Testing 2
+```
+Enter your polynomial: 11 15 19 21
+Enter your K: 29
+           0     1     2
+0  11.000000  19.0  29.0
+1  15.000000  21.0   0.0
+2   3.600000  29.0   0.0
+3 -99.833333   0.0   0.0
+4  29.000000  -0.0   0.0
+SYSTEM IS UNSTABLE
+```
+
+## Testing 3
+```
+Enter your polynomial: 1.2 6.78 11.11
+Enter your K: 3.141
+           0       1
+0   1.200000  11.110
+1   6.780000   3.141
+2  10.554071   0.000
+3   3.141000   0.000
+SYSTEM IS STABLE
+```
+### Notes
+Contact nanda.r.d@mail.ugm.ac.id for more information
+### Links
+You can access the source code here
+[github.com/nandard/routh_table.git](https://github.com/nandard/routh_table.git)
\ No newline at end of file
diff --git a/Assignment 4 - PI/README.md b/Assignment 4 - PI/README.md
new file mode 100644
index 0000000..47f5995
--- /dev/null
+++ b/Assignment 4 - PI/README.md	
@@ -0,0 +1,69 @@
+# Integral Effect on Control System
+This dir is belong to Control System class contains with Integral Effect on Control System. This code 100% original made by my hand :), please leave some notes if you're going to use it. Thanks!
+
+## Software
+This program run in Matlab
+
+## Variables
+`s = tf('s');` defines s as 'frequency domain' for transfer function and will be used further. 
+```
+J = 0.01;
+b = 0.1;
+K = 0.01;
+R = 1;
+L = 0.5;
+```
+Those variable comes from BLDC control system.
+```
+Kp = 1;
+% Ki = 1;
+% Ki = 3;
+% Ki = 5;
+ Ki = 7;
+% Ki = 9;
+```
+Variable above is the constant from PI control, we're trying to varies the constant to analyze integral effect on control system
+
+## Process
+The BLDC motor control system should be defined as transfer function by initialize its numerator-denumerator and *tf()* function.
+```
+num_motor = [K];
+den_motor = [J*L J*R+b*L R*b+K*K];
+
+motor = tf(num_motor,den_motor)
+```
+Besides the plant function, the PI-control system defined by `C = tf([Kp Ki],[1 0])`. The vector is set according to PI formula which `PI = Kp * Ki/s`. After that, both of system are multiplied each others without feedback by `complete = feedback(motor*C,1);`
+
+That system will be test with step, ramp, and impulse input by call below lines
+```
+subplot(311), impulse(complete);   % Impulse reponse
+subplot(312), step(complete);      % Step Response
+subplot(313), step(complete / s);  % Ramp response
+stepinfo(complete)
+```
+
+Since Matlab doesn't provide any steady-state error calculation, we process it by call below lines
+```
+[y,t] = step(complete); % Calculate Steady-State error
+sse = abs(1 - y(end))
+```
+Last line works to limit the graph
+```
+xlim([0 50])
+ylim([0 3])
+```
+
+
+## Testing 
+|   Kp = 1	|   Ki = 1	|   Ki = 3	|   Ki = 5	|   Ki = 7	|   Ki = 9	|
+|---	|---	|---	|---	|---	|---	|
+|   Rise Time	|   22.7723	|   6.7782	|   3.5914	|   2.3175	|   2.3175	|
+|   Settling Time	|   40.3716	|   12.1907	|   6.3158	|   3.6779	|  3.6779 	|
+|   Overshoot	|   0	|   0	|   0	|   0.3523	|   0	|
+|   SSE	|   1.7396e-06	|   0.0034	|   0.0033	|   0.0034	|   6.6536e-05	|
+
+### Notes
+Contact nanda.r.d@mail.ugm.ac.id for more information
+### Links
+You can access the source code here
+[github.com/nandard/routh_table.git](https://github.com/nandard/routh_table.git)
\ No newline at end of file
diff --git a/Assignment 4 - PI/integral_tf.m b/Assignment 4 - PI/integral_tf.m
new file mode 100644
index 0000000..32f59ba
--- /dev/null
+++ b/Assignment 4 - PI/integral_tf.m	
@@ -0,0 +1,35 @@
+% Variable
+s = tf('s');
+J = 0.01;
+b = 0.1;
+K = 0.01;
+R = 1;
+L = 0.5;
+
+Kp = 1;
+% Ki = 1;
+% Ki = 3;
+% Ki = 5;
+ Ki = 7;
+% Ki = 9;
+
+% Define Transfer Function
+num_motor = [K];
+den_motor = [J*L J*R+b*L R*b+K*K];
+
+motor = tf(num_motor,den_motor)
+% Define Control Function
+C = tf([Kp Ki],[1 0])
+% Define Closed-Loop function
+complete = feedback(motor*C,1);
+% Process system responses
+subplot(311), impulse(complete);   % Impulse reponse
+subplot(312), step(complete);      % Step Response
+subplot(313), step(complete / s);  % Ramp response
+stepinfo(complete)
+% Calculate the Stead-State Error
+[y,t] = step(complete); % Calculate Steady-State error
+sse = abs(1 - y(end))
+% Limit the graph
+xlim([0 50])
+ylim([0 3])
\ No newline at end of file
diff --git a/README.md b/README.md
index d2f6212..8d4da26 100644
--- a/README.md
+++ b/README.md
@@ -1,132 +1,6 @@
 # routh_table
-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!
+This repo is belong to Control System class and Mr. Muhammad Auzan as lecturer. This code 100% original made by my hand :), please leave some notes if you're going to use it. Thanks!
 
-## Libraries
-Libraries that used in this program is ```numpy``` and ```pandas```. ```numpy``` works to define and perform array while ```pandas``` is the final form after ```numpy.array``` to simplify the presentation. They imported by write..
-```
-import numpy as np
-import pandas as pd
-```
-
-## RouthStability Class
-This class contains lots of procedures to simplify our Routh Stability Table Generator process. 
-```
-def __init__(self, den):
-    self.den = np.array([float(item) for item in den.split()])
-    self.deg = len(self.den)
-```
-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 to calling ```len()``` function
-
-```
-def set_k(self, k):
-    self.den = np.append(self.den, float(k))
-    self.deg += 1
-```
-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
-
-```
-def calc_routh(self):
-    height = (self.deg+1)//2
-    arr = np.zeros((height + 2,height))
-    for index in range(self.deg):
-        if index % 2 == 0:
-        arr[0][index//2] = self.den[index]
-        else:
-        arr[1][(index-1)//2] = self.den[index]
-
-    for i in range(2, height+2):
-        for j in range(height-1):
-        arr[i][j] = (arr[i-1][0]*arr[i-2][j+1] - arr[i-2][0]*arr[i-1][j+1])/arr[i-1][0]
-        arr[i][j] += 0
-
-    self.df = pd.DataFrame(arr)
-    self.show_tab()
-    if self.is_stable() == True:
-        print("SYSTEM IS STABLE")
-    else:
-        print("SYSTEM IS UNSTABLE")
-```
-```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.
-
-```
-def show_tab(self):
-    print(self.df)
-```
-This function print the Routh Table, should be called only if Routh Table is generated by ```calc_routh```
-
-```
-def get_table(self):
-    return self.df
-```
-This function return ```pandas.DataFrame``` contained by Routh Table
-
-```
-def is_stable(self):
-    flag = True
-    for item in self.df[0]:
-        if item < 0: flag = False
-    return flag
-```
-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
-
-```
-def get_poly(self, x):
-    total = 0
-    for i in range(self.deg):
-        total += self.den[self.deg-i-1]*(x**i)
-        print(total)
-    return total
-```
-This function initialize ```x``` value as variable on ```self.den``` polynomial and return the total
-
-## Testing 1
-The testing can follow below example:
-```
-# First Testing
-den = input("Enter your polynomial: ")
-k_in = input("Enter your K: ")
-
-rs = RouthStability(den)
-rs.set_k(k_in)
-rs.calc_routh()
-```
-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:
-```
-Enter your polynomial: 1 3 5 7
-Enter your K: 9
-          0    1    2
-0  1.000000  5.0  9.0
-1  3.000000  7.0  0.0
-2  2.666667  9.0  0.0
-3 -3.125000  0.0  0.0
-4  9.000000 -0.0  0.0
-SYSTEM IS UNSTABLE
-```
-
-## Testing 2
-```
-Enter your polynomial: 11 15 19 21
-Enter your K: 29
-           0     1     2
-0  11.000000  19.0  29.0
-1  15.000000  21.0   0.0
-2   3.600000  29.0   0.0
-3 -99.833333   0.0   0.0
-4  29.000000  -0.0   0.0
-SYSTEM IS UNSTABLE
-```
-
-## Testing 3
-```
-Enter your polynomial: 1.2 6.78 11.11
-Enter your K: 3.141
-           0       1
-0   1.200000  11.110
-1   6.780000   3.141
-2  10.554071   0.000
-3   3.141000   0.000
-SYSTEM IS STABLE
-```
 ### Notes
 Contact nanda.r.d@mail.ugm.ac.id for more information
 ### Links