FYP 2 SLIDE

MODELLING , CONTROL AND NAVIGATION OF AN
AUTONOMOUS QUADROTOR UAV
(MODELLING AND CONTROL)
SITI FATIRAH BINTI RAMLI
1120486
SUPERVISED BY DR. MOUMEN IDRES

CONTENT OVERVIEW
 INTRODUCTION
 PROBLEM STATEMENT
 OBJECTIVES
 LITERATURE REVIEW
 METHODOLOGY
 RESULTS
 CONCLUSION

INTRODUCTION
 Quadrotor is a symmetrical flying machines which has 4 rotors at
each end of its body frame
 Quadrotor is a a Vertical Take Off and Landing (VTOL) type landing
machine
 Quadrotor need a controller in order to fly : PID controller
 Controller is a heart or brain of quadrotor
 Function of controller is to give command to quadrotor in order to fly
or doing a mission

PROBLEM STATEMENT
 A stable quadrotor need a controller to fly
 The quadrotor is going to perform a better autonomous control
 The implementation of PID controller will be studied to enhance the
quadrotor stability and maneuverability

OBJECTIVES
 To develop a mathematical modeling of quadrotor
 To study the controller that used to fly the quadrotor in the air

LITERATURE REVIEW
PID Controller LQR Controller
 feedback controller
 based on the error (e) between
desired set point and measured
process value
 The error is then used to adjust
some input to the process in
order to its defined set point
 LQR is a control scheme
 provides the best possible
performance with respect to
some given measure of
performance
 Need to design statefeedback
controller which minimise the
objective function

METHODOLOGY
Parameters
identification
Mathematical
modeling of
quadrotor
Controller of
quadrotor
Simulation in
Matlab
FYP 1 FYP 2

 Through experimental and calculation method
 The parameters that have been identified are
torque constant , 𝑘 𝑡
moment of inertia around x, y and z axes , 𝐼 𝑥𝑥, 𝐼 𝑌𝑌 and 𝐼𝑧𝑧
rotor inertia
drag coefficient
mass of quadrotor
length of arm of quadrotor, la
gravity , g
Parameter Identification

 Need to establish the frames which are inertial frame and body frame
 Equations of motions of quadrotor is important as it moves in 6 DoF
Mathematical Modelling of quadrotor
Translational kinematics for doing a transformation matrix as
position is describe in inertial frame while
velocity is describe in body frame
Rotational Kinematics used in determining the relationship
between angular rates and time derivatives
of Euler angles
Translational Dynamics used to calculate the value of acceleration
,drag force and resultant force by four
rotors in inertial frame
Rotational Dynamics used for to calculate moment of inertia in x,
y, z axes

Controller of quadrotor
Simple PID Controller for Quadrotor

Block Diagram of PID Controller for Quadrotor in Simulink

 Using a Matlab 2013 for the simulation part
 Block diagram done in Simulink
 Coding for the controller being edited in Matlab editor as the coding is
been altered from Mr. WilCelby research on quadrotor controller
 The coding is altered to meet our desired goal
Simulation in Matlab
Point 1
Point 3Point 4
Point 2

RESULTS
 Parameters for quadrotor
 Has 3 part for results which are
1. Translational Position PID Controller
2. Altitude/Attitude PID Controller
3. Angular Rate PID Controller

Parameters for quadrotor
Parameters Value Unit Remarks
𝑘 𝑡 3.7 10-3 Nm/A torque constant
𝐼 𝑥𝑥 = 𝐼 𝑌𝑌
𝐼𝑧𝑧
6.0712 × 10−2
0.1157792
𝑘𝑔𝑚2
𝑘𝑔𝑚2
moment of inertia
IR 3.357 .10-5 kgm2 rotor inertia
cd 1 - drag coefficient
m 1.4 kg mass of quadrotor
la 0.36 m length of arm of quadrotor
g 9.81 m/s2 Gravity

RESULTS
POINT 1 [ 0 0 0] TO [1 1 -1]

P𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑒𝑟𝑟𝑜𝑟 =
|𝑇ℎ𝑒𝑜𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑣𝑎𝑙𝑢𝑒−𝐸𝑥𝑝𝑒𝑟𝑖𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑎𝑙𝑢𝑒|
𝑇ℎ𝑒𝑜𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑣𝑎𝑙𝑢𝑒
× 100%
where Theoritical value = TranslationalPositionDesired
Experimental value = Simulation output
Percentage error
calculation
Percentage error
x |1 − 1.0016|
1
× 100%
0.16%
y |1 − 0.9829|
1
× 100%
1.71%
z |1 − 0.9785|
1
× 100%
2.16%

POINT 2 [ 1 1 -1 ] TO [ 2 1 -1 ]

Percentage error
calculation
Percentage error
x |2 − 1.9934|
2
× 100%
0.33%
y |1 − 1.0128|
1
× 100%
1.28%
z |1 − 1.0033|
1
× 100%
0.33%

POINT 3 [ 2 1 -1 ] TO [ 2 2 -1 ]

Percentage error
calculation
Percentage error
x |2 − 2.0140|
2
× 100%
0.7%
y |2 − 1.9975|
2
× 100%
0.125%
z |1 − 1.0256|
1
× 100%
2.56%

POINT 4 [ 2 2 -1 ] TO [ 1 2 -1 ]

Percentage error
calculation
Percentage error
x |1 − 1.0036|
1
× 100%
0.36%
y |2 − 1.9938|
2
× 100%
0.31%
z |1 − 0.9863|
1
× 100%
1.37%

POINT 5 [ 1 2 -1 ] TO [ 1 1 -1 ]

Percentage error
calculation
Percentage error
x |1 − 0.9875|
1
× 100%
1.25%
y |1 − 1.0199|
1
× 100%
1.99%
z |1 − 0.9986|
1
× 100%
0.14%

Angular rate PID Controller
POINT 1 POINT 2
POINT 3 POINT 4

CONCLUSION
 Objectives have been achieved
 PID controller is the optimal controller to be used in control
system of quadrotor

FYP 2 SLIDE

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