Aerospace and Electronic Systems Magazine June 2017 - 61

Student Research Highlights:

DOI. No. 10.1109/MAES.2017.160060

Quadrotor Electronics and Intelligent Control
Allen Babb, Muhittin Yilmaz, Texas A&M University-Kingsville, Kingsville, TX, USA

INTRODUCTION
Unmanned aerial vehicles (UAVs) have seen diverse applications,
including radiation or border surveillance, with quadrotors offering small size, relatively low cost, high mobility, mass production,
and easy access to challenging environments. In addition, quadrotors can carry sensors, cameras, or other gadgets for information
collection, data fusion, and subsequent actions of targets, as was
exemplified during the Fukushima nuclear plant disaster, by visual
and sensory surveillance or for an air delivery system.
UAVs have also spurred extensive research on physical design,
operation principles, components, and control algorithms, partially
due to complex stabilization problems, including the Stanford testbed of autonomous rotorcraft for multiagent control [1] quadrotor with linear controllers for position control systems, the X-4
flyer [2] with discrete model controllers, and the MikroKopter [3]
with an open-source code development, as well as implementation and control with state estimation. Inherently nonlinear UAV
dynamics can also be governed by intelligent controllers that can
handle complex, nonlinear systems for superior outcomes. As an
intelligent framework, fuzzy logic (FL) reflects real-life vagueness
and imprecise data to provide decisions via nonlinear mapping via
fuzzy sets, rules, and membership functions [4].
This project describes the development and implementation of
a practical, low cost, lightweight quadrotor electronic test platform
design to evaluate the FL closed-loop controller for roll and pitch
stabilization.

QUADROTOR DEVELOPMENT
The AirDragon quadrotor was conceptually designed and built using commodity products. The Freescale 16-bit MCS9S12DG256
microcontroller unit (MCU) was implemented on the MicroDragon breakout board made by EVBplus. With superior features, the
MCU unit has the serial monitor for CodeWarrior (Freescale),
Authors' current address: Texas A&M University-Kingsville,
Electrical Engineering and Computer Science, 700 University
Blvd. MSC 192, ENGC 322, Kingsville, TX 78363 USA, E-mail:
(muhittin.yilmaz@tamuk.edu).
The project was partially supported by the National Science
Foundation, grant EEC-0908672, Research Experience for
Teachers in Manufacturing for Competitiveness in the United
States.
Manuscript received March 4, 2016, revised July 2, 2016, September 14, 2016, and ready for publication June 15, 2016.
Review handled by J. Glass.
0885/8985/17/$26.00 © 2017 IEEE
JUNE 2017

the software development tool used during the project, and provides built-in FL control design tools. The inertial measurement
unit (IMU) was an Analog Combo Board Razor from SparkFun
and used two microelectromechanical system (MEMS) gyros for
pitch, roll, and yaw rate detection and one 3-axis MEMS accelerometer (Figure 1). The electronic speed controller (ESC) was a
low-cost BP 18A Brushless ESC from BP Hobbies, featuring an
8-kHz pulse-width modulation (PWM) for driving the motor and a
self-adjusting throttle range. The MCU unit sends a PWM signal to
the ESC module to set the desired speed of the motor. The motors
were four BP A2212-13 brushless DC Outrunner motors with high
power-to-weight ratios and lower noise levels, as compared with
conventional brushed DC motors. Four 25-cm-long Slow Flyer
electric propellers by APC were attached for sufficient quadrotor
lift for indoor demonstrations. Battery power was provided by two
E-flite 3S 2200-mAh lithium polymer batteries for extended testing and weight balancing. The MCU and IMU are powered by two
voltage regulators that step down the 11.1-V battery voltage to 5 V
and 3.3 V, respectively. The chassis was built by using four 30-cmlong aluminum rods and three round polycarbonate plates. The
rods were affixed to the panels by using custom-milled clamps and
a center mounting bracket. The motors were attached to the rods
by using clamplike motor mounts, allowing for various configurations that are useful when extra batteries or payloads are needed.
The quadrotor components were ordered, the case of the power and
PWM distribution boards were soldered together, and the quadrotor was assembled in steps, given in Figure 2.
The quadrotor MCU used both C and assembly languages to
implement the operation system and the control algorithms. The
majority of hardware configuration and controller code scheduling was implemented in the C code. The FL controller was written in the MCU assembler language to make use of its built-in FL
function library, resulting in fastest execution performance, critical
during the real-time quadrotor stabilization. The operation system
software was first started by initializing the MCU system clock
to 24 MHz. Then, the enhanced capture time and PWM modules
were initialized. Next, the set of global system variables, such as
throttles and interrupt service routine counters, were initialized.

Figure 1.

The quadrotor system major components: (left to right) the IMU, the
electronic speed controller, the brushless DC motor, and the LiPo battery.

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