From 1059a7f79187182c6a9dc933197017b49e4e44f0 Mon Sep 17 00:00:00 2001
From: Alvie Rahman <alvierahman90@gmail.com>
Date: Wed, 6 Dec 2023 15:20:58 +0000
Subject: [PATCH] expand q2, fix formatting

---
 src/submission.md | 32 +++++++++++++++++++++++---------
 1 file changed, 23 insertions(+), 9 deletions(-)

diff --git a/src/submission.md b/src/submission.md
index 2c798d5..ec98194 100755
--- a/src/submission.md
+++ b/src/submission.md
@@ -11,8 +11,6 @@ geometry:
 \maketitle
 \thispagestyle{empty}
 \newpage
-\tableofcontents
-\newpage
 
 # Question 1
 
@@ -27,8 +25,11 @@ maybe not push enough current to motor to actually get it spinning in some cases
 # Question 2
 
 When derivative control is added at low levels (0.02) it reduces the oscillations.
+
 This is because derivative control only considers the rate of change of of the error
-and therefore tries to bring the rate of change to zero.
+and tries to bring the rate of change to zero.
+This means that adds a *damping* effect to the controller, slowing it down when it's moving,
+and thereby reducing/eliminating overshoot and oscillations.
 
 # Question 3
 
@@ -68,18 +69,23 @@ Some initialisation is run in `setup` on lines 89 and 90:
 Then the main control loop starts.
 The `loop` function runs the `controlLoop` function every 20 milliseconds (as defined by
 `controlInterval`) on line 101.
+
 The `controlLoop` function retrieves the current motor position and stores it in the variable
 that the PID controller has a pointer to.
+
 `myPID.Compute()` is then called to recompute the motor speed required to get to the set point
 and this is stored in the `percentSpeed` variable as the controller has a pointer to it.
 This new speed is passed to the `driveMotorPercent` function to update the motor's speed.
 
+\newpage
+
 # Question 5
 
 The mathematically complex operations in `loop()` as it is run infrequently.
 This is because it is inside an if statement with condition `convertNewNumber()`, which
 returns `false` if there is no new data to convert (i.e. if there has not been any serial input
 since the last loop).
+
 Essentially, the complex operations only run once per serial input, meaning it is run very infrequently
 compared to how many times the loop runs.
 
@@ -104,9 +110,11 @@ of the shaft, as the magnets of the motor will not be aligned as needed.
 This is also why the steppers use a ramp function, so that the shaft has time accelerate to the
 desired speed without skipping steps.
 
+\newpage
+
 # Question 8
 
-```{ .matplotlib caption="A plot of velocity and acceleration for SimplisticRampStepper" dpi=150 }
+```{ .matplotlib caption="A plot of velocity and acceleration for SimplisticRampStepper" dpi=300 }
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -122,17 +130,20 @@ data = np.genfromtxt("csv/SimplisticRampStepper_out_50.csv",
 fig, ax1 = plt.subplots()
 ax2 = ax1.twinx()
 
-ax1.plot(data[TIME], data[SPEED], label='Speed [steps/s]', color='tab:blue')
-ax2.plot(data[TIME], data[ACCEL], label='Acceleration [steps/s^2]', color='tab:red')
+lines1 = ax1.plot(data[TIME], data[SPEED], label='Speed [steps/s]', color='tab:blue')
+lines2 = ax2.plot(data[TIME], data[ACCEL], label='Acceleration [steps/s^2]', color='tab:red')
 ax1.set_ylabel('Speed [steps/s]')
 ax2.set_ylabel('Acceleration [steps/s^2]')
 
+lines = lines1 + lines2
+ax1.legend(lines, [ l.get_label() for l in lines ])
+
 ax1.set_xlabel("Time [s]")
 
 fig.tight_layout()
 ```
 
-```{ .matplotlib caption="A plot of velocity and acceleration for LeibRampStepper" dpi=150 }
+```{ .matplotlib caption="A plot of velocity and acceleration for LeibRampStepper" dpi=300 }
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -148,11 +159,14 @@ data = np.genfromtxt("csv/LeibRampStepper_out_50.csv",
 fig, ax1 = plt.subplots()
 ax2 = ax1.twinx()
 
-ax1.plot(data[TIME], data[SPEED], label='Speed [steps/s]', color='tab:blue')
-ax2.plot(data[TIME], data[ACCEL], label='Acceleration [steps/s^2]', color='tab:red')
+lines1 = ax1.plot(data[TIME], data[SPEED], label='Speed [steps/s]', color='tab:blue')
+lines2 = ax2.plot(data[TIME], data[ACCEL], label='Acceleration [steps/s^2]', color='tab:red')
 ax1.set_ylabel('Speed [steps/s]')
 ax2.set_ylabel('Acceleration [steps/s^2]')
 
+lines = lines1 + lines2
+ax1.legend(lines, [ l.get_label() for l in lines ], loc='upper right')
+
 ax1.set_xlabel("Time [s]")
 
 fig.tight_layout()