QUAD-COPTERA DREAM PROJECT…

Project supervisor and our guide:-Mr. Shashi Poddar (Sr. Scientist Avionics-CSIO)

Overview•Introduction•Structure of quadcopter•Design of quadcopter•Architecture•Control theory•Sensor fusion•PID controller•Safety Algorithms•Future development and implementation•Conclusions

Introduction •“To fly” has been one of the dreams of the humans

•But the story tells that building flying machines is not easy!

•A basic and common component: the wing

•Two kind of “flying machines” (excluding rockets and balloons):

1. Fixed wing, i.e. airplanes2. Rotating wing, i.e. helicopters

Why Multi-rotors ...•Are mechanically simple: they have n motors and n

propellers•Do not require complex mechanical parts to control the

flight•Can fly and move only by changing motor speed•Are controlled only by a electronic-/computer-based

system

Structure of quadcopter• Mechanical :- A frame, 4 brushless motors (with frame pads and

propeller adapter), 4 rotors (two clockwise two counter clockwise), 4 esc, Screw pack and instruments.

• Electronics :-A control board, battery, and radio receiver, some sensor (gyroscope, accelerometer, barometer, pressure measurement) or IMU (inertial measurement unit).

Design of quadcopter

• Four equal propellers generating four thrust forces• Two possible configurations: “+” and “× ”• Propellers 1 and 3 rotates CW, 2 and 4 rotates CCW• Required to compensate the action/reaction effect (Third Newton’s Law)• Propellers 1 and 3 have opposite pitch w.r.t. 2 and 4, so all thrusts have

the same direction

DYNAMICS(FORCES AND ROTATION SPEED)• ω1 , ω2, ω3, ω4: rotation speeds of the propellers• T1 , T2, T3, T4: forces generated by the propellers• Ti ∝ ωi2: on the basis of propeller shape, air density, etc.• mg: weight of the Quadrotor• M1 , M2, M3, M4: moments generated by the forces Mi = L × Ti• PITCH= θ• ROLL= φ• YAW= ψ

HOVERING CONDITION• 1 Equilibrium of forces: ∑4

i=1 Ti = −mg(Violating gives thrust)• 2 Equilibrium of directions: T1 ,2,3,4 ||g• 3 Equilibrium of moments: ∑4

i=1 Mi = 0• 4 Equilibrium of rotation speeds: (ω1 + ω3) − (ω2 + ω4) = 0 (Violating gives Yaw)

• Violating one (or more) of these conditions implies to impose a certain movement to the Quadrotor

• As a consequence:φ = 0 θ = 0 ψ = 0

ArchitectureUser

PC(ground station)

Transceiver

Base Station

Transceiver

Camera(wireless)

Motors

Gyroscopes

Accelerometers

Magnetometer

Pressure Sensor

Quadrotor

Attitude PID

Angle Estimat

e

Correction

Translation PID

Reference

Microcontroller

SCHEMATIC

CONTROL THEORY

CONTROL THEORYSame PWM signals applied different driver/motor/propellerchains provoke different thrust forces, even if the componentsare of the same type!

Solution!!!! Use feedback!1 Measure your variable through a sensor2 Compare the measured value with your desired set point3 Apply the correction to the system on the basis of the error4 Go to 1

CONTROL THEORY•In our scenario

▫Our measures Actual angular velocities on the three axis (φ, θ, ψ) They are measured through a 3-axis gyroscope!, accelerometer

and magnetometer

▫Our set points Desired angular velocities on the three axis (φ˙T, θ˙T, ψ˙T) They are given through the remote control

CONTROL THEORY

FEEDBACK CONTROLLER-(P.I.D. CONTROLLER)•The most common used controller type is the

Proportional-Integral-Derivative controller▫WHY PID?

THE ANSWER IS WHY NOT If we only feed the error overcoming thrust value into controller its

inertia will overcompensate the error and new error will be generated and quadcopter will remain oscillating continuosly.

To reduce this error we should apply a controller which resist the change while overcompensating which is perfectly done by derivative control

And the oscillation is damped by integrating control.

PID CONTROLLER•PID control is shown in block diagram form in Figure and is

performed in the following steps: The error e(t) is calculated as Set point – Measured State The proportional term P is calculated as [Kp * e(t)] The integral term I is calculated as [KI * The derivative term D is calculated a [KD * (e(t))] where is previous

error value The 3 terms are summed to produce the controller output, u(t) = P +

I + D•In order to stabilize the quadcopter, a separate PID controller

was implemented for the roll, pitch, and yaw axes.

PID CONTROLLER

SENSOR FUSION (WHY?)•Accelerometer gives us an absolute measurement of the

quadcopter orientation, but accelerometers are very prone to noise. The motors on the quadcopter produce a lot of vibration, introducing significant noise into the accelerometer reading.

•The gyroscope is much less effected by vibration, but it only gives us angular rotation rates.

•By integrating the gyroscope readings, it is possible to estimate the orientation , but this reading is prone to drifting over time.

SENSOR FUSION(COMPARE)

0 10000 20000 30000 40000 50000 60000

-100-80-60-40-20

020406080

100

ACCELEROMETER

0 10000 20000 30000 40000 50000 60000

-200

-150

-100

-50

0

50GYROSCOPE

0 10000 20000 30000 40000 50000 60000

-150

-100

-50

0

50

100

150

REAL ANGLE

SENSOR FUSION

0 10000 20000 30000 40000 50000 60000

-200

-150

-100

-50

0

50

100

150

A R G RROLL

THIS ALGORITHM CONTINOUSLY CHECKS THE ANGLE OF GYROSCOPE ANGLE WITH ACCELEROMETER ANGLE AND ELEMINATE THE DRIFT ERROR OF GYROSCOPE