Quadcopter final report anand
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This document provides an overview of a quadcopter project. It introduces the project supervisor and describes the structure, design, control theory, and sensors of a quadcopter. It explains that quadcopters use four motors and propellers for lift and are controlled electronically rather than with complex mechanical systems like helicopters. It also discusses the PID control algorithm used to stabilize the quadcopter based on sensor feedback and error calculations. Sensor fusion is described as important for combining gyroscope and accelerometer readings to reduce noise and drift in the orientation estimates.
![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 * 𝑡=0
𝑡=𝑛
e(t)]
The derivative term D is calculated a [KD * (e(t) −e(t))] where e(t) 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.](https://image.slidesharecdn.com/quadcopterfinalreportanand-160729095513/85/Quadcopter-final-report-anand-16-320.jpg)
Quadcopter final report anand
- 1. Project supervisor and our guide:- Mr. Shashi Poddar (Sr. Scientist Avionics-CSIO)
- 2. Overview • Introduction • Structure of quadcopter • Design of quadcopter • Architecture • Control theory • Sensor fusion • PID controller • Safety Algorithms • Future development and implementation • Conclusions
- 3. 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. airplanes 2. Rotating wing, i.e. helicopters
- 4. 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
- 5. 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).
- 6. 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
- 7. 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
- 8. 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
- 10. SCHEMATIC
- 11. CONTROL THEORY
- 12. CONTROL THEORY Same PWM signals applied different driver/motor/propeller chains provoke different thrust forces, even if the components are of the same type! Solution!!!! Use feedback! 1 Measure your variable through a sensor 2 Compare the measured value with your desired set point 3 Apply the correction to the system on the basis of the error 4 Go to 1
- 13. 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
- 14. CONTROL THEORY
- 15. 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.
- 16. 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 * 𝑡=0 𝑡=𝑛 e(t)] The derivative term D is calculated a [KD * (e(t) −e(t))] where e(t) 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.
- 17. PID CONTROLLER
- 18. 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.
- 19. SENSOR FUSION(COMPARE) -100 -80 -60 -40 -20 0 20 40 60 80 100 0 10000 20000 30000 40000 50000 60000 ACCELEROMETER -200 -150 -100 -50 0 50 0 10000 20000 30000 40000 50000 60000 GYROSCOPE -150 -100 -50 0 50 100 0 20000 40000 60000 REAL ANGLE
- 20. SENSOR FUSION -200 -150 -100 -50 0 50 100 150 0 10000 20000 30000 40000 50000 60000 A R G R ROLL THIS ALGORITHM CONTINOUSLY CHECKS THE ANGLE OF GYROSCOPE ANGLE WITH ACCELEROMETER ANGLE AND ELEMINATE THE DRIFT ERROR OF GYROSCOPE