The document describes a quadcopter design project created by students Marc Salas, Micah Lucas, and Rudra Timsina, advised by Dr. Richard Messner. The objective was to design a robust quadcopter that can easily be modified with new components and software. Key components included an Arduino flight controller, electronic speed controllers, a radio receiver, and sensors. A PID controller was implemented for stability using gyroscope feedback. Future work may include adding GPS, cameras, and obstacle avoidance capabilities.

1. Project Team: Marc Salas, Micah Lucas, Rudra Timsina
Advisor: Dr. Richard Messner
Department of Electrical Engineering, University of New Hampshire, Durham, NH
Current market quadcopters do not offer the
ability to add or prototype custom components
like GPS or video streaming.
Our objective was to come up with a robust
quadcopter design that can easily be modified to
include new components and software.
Arduino Mega 2560 R3
The arduino acts as a flight controller. It keeps
the quadcopter stable in the air and also
processes the control signals from the radio
controller. It is also a critical device because it
allows multiple sensors and devices to be easily
implemented in the quadcopter.
Electronic Speed Controller (ESC)
Converts the PWM output of the arduino to the
appropriate signal needed by the motors
Receiver Module (AR6210 6-Channel
DSMX Receiver)
Reads the signal from the handheld controller
and sends PWM signals to the arduino.
Inertial Measurement Unit
(ITG3200/ADXL345)
This includes a digital gyroscope and an
accelerometer and gives the quadcopter feedback
so it knows it’s orientation and position in space.
The feedback is a sensed error in roll, pitch, and
yaw angles.
Problem definition
Objective
Methods and Materials
The receiver interprets the pulse width modulated (PWM)signals from the controller. The PID uses these signals as the throttle input and angle
“setpoints”. The “setpoint “is the desired angle of orientation for the quadcopter. The ESC’s convert the PID output into the signal needed to operate the
motors. The Gyroscope senses the error in angular orientation and provides feedback to the PID.
Block Diagram
Controller Receiver
Arduino
ESCPID( input, output, setpoint, Kp, Ki, Kd) Motors
Digital
Gyroscope

0 0.5 1 1.5
-35
-30
-25
-20
-15
-10
-5
0
5
Time
Orientation(degrees)
Step Response
Roll
Pitch
Step Response
Time
Amplitude
0 2 4 6 8 10 12 14 16 18
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Step Response of a Closed Transfer Function
The stability of the quadcopter is
maintained using a proportional-
integral-derivative (PID) controller.
The PID controller minimizes the
output error by adjusting the control
input. The proportional gain affects
the system based on the present error,
integral gain, on past error, and
derivative gain, on predicted future
error.
Stability
Model Prediction
System Features
Left: The step response after PID was realized.
Right:The change in the orientation of a quadcopter with a step response without using PID
 Implement a GPS for autonomous flight.
Realize range finders for obstacle avoidance.
Add camera for video surveillance.
Implement more advance stability control scheme.
Can easily lift up to an additional pound and a half.
Controller range of over 1 km.
Over 15 minutes of continuous flight time.
Future Improvements
Program Flow chart
A fifth order transfer function was estimated
using MATLAB system identification tool.
The PID values were estimated based on PID
tuner in MATLAB.
10
-3
10
-2
10
-1
10
0
10
1
10
2
10
3
10
4
10
5
-180
0
180
360
540
720
Phase(deg)
Bode Diagram
Gm=54.6 dB (at 10.1 rad/s) , Pm=Inf
Frequency (rad/s)
-100
-80
-60
-40
-20
0
From: u1 To: y1
Magnitude(dB)
Frequency response of the predicted modal.
Gyro axis of the quadcopter
Real Axis
ImaginaryAxis
-1 -0.5 0 0.5 1 1.5
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
From: Step To: Transfer Fcn
0 dB
-20 dB
-10 dB
-6 dB
-4 dB-2 dB
20 dB
10 dB
6 dB
4 dB 2 dB linsys7
Nyquist plot for the modal.