Smart Control Algorithm for 2-DOF Helicopter

Glenn Janiak Kenneth Vonckx Advisor: Dr. Suruz Miah

Department of Electrical and Computer EngineeringBradley University

1501 W. Bradley AvenuePeoria, IL, 61625, USA

Thursday, November 29, 2018

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Introduction

Helicopter are important for short-distance travel

air-sea rescuefire fightingtraffic controltourism

Purpose of control system

resistance to turbulenceenable use of mobile device

Which is better?

Fundamental (LQR)Noise Filtering (LQG)Machine Learning (ADP)

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Introduction

Helicopter 1

Helicopter 2

Helicopter N

Proposed

smart control

algorithm of

helicopters

Mobile

device 1

Mobile

device 2

Mobile

device N

Wireless

network

Figure 1: General High-Level System Architecture

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Introduction

This project will:

use a pair of 2-DOF (2-degrees-of-freedom) testing platformsimplement control algorithms on embedded systemuse mobile device for user controlencourage researchserve as an educational tool

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Background StudyControl Techniques

Various control techniques have been proposed for 2-DOF helicopters suchas:

Sliding mode control [1]

Fuzzy Logic control [2] [3] [4]

Data-driven Adaptive Optimal Output-feedback control [5]

Decentralized discrete-time neural control [6]

These control techniques employ advanced mathematics that are difficultto implement on embedded systems.

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Background StudyModeling a 2-DOF Helicopter

Figure 2: Model of a 2-DOF Helicopter

Figure 3: Quanser Aero

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Background StudyModeling a 2-DOF Helicopter

Characterized by fixed baseCan change 2 of 3 possible orientations...

Pitch (θ)Yaw (ψ)Not Roll

and cannot change position

x directiony directionz direction

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Background StudyModeling a 2-DOF Helicopter

Motors are attached to the propellers to create thrust due to airresistance

Main - changes pitch angleTail - changes yaw angle

Torque due to rotation also creates a force on opposite axes

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Background StudyModeling a 2-DOF Helicopter

ẋ(t) = Ax(t) + Bu(t), where (1)

A =

0 0 1 00 0 0 1

−KspJp 0 −DpJp

0

0 0 0 −DyJy

and B =

0 00 0KppJp

KpyJp

KypJy

KyyJy

,

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Background StudyModeling a 2-DOF Helicopter

Ksp - being the stiffness of the axes

Kpp - pitch motor thrust constant

Kpy - thrust constant acting on the pitch angle from the yaw motor

Kyp - thrust constant acting on the yaw angle from the pitch motor

Kyy - yaw motor thrust constant

Jp - moment of inertia about pitch axis

Jy - moment of inertia about yaw axis

Dp - viscous damping of the pitch axis

Dy - viscous damping of the yaw axis

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Background StudyPrior Work

extensive modeling & simulations

implementation of two motion control algorithms (LQR & ADP)

one helicopter

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Subsystem Level Functional RequirementsBlock Diagram

Application

Transport

Link

Internet

Application

Transport

Link

Internet

Mobile Device Raspberry Pi

Data

Data

Data

Data

UDP

UDP

UDP

IP

IPMAC

Controller

(packet sent through air)

Data

DataUDP

DataUDPIP

DataUDPIPMAC

Figure 4: Communication Model

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Subsystem Level Functional RequirementsBlock Diagram

Select

algorithm

Actual pitch

Desired pitch

Desired yaw

Actual yaw

Pitch motor

Yaw motor

Pitch encoder

Yaw encoder

LQG

LQR

ADP

Figure 5: Low Level Smart Control Diagram

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Preliminary WorkLQR Simulation

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Time [s]

0

5

10

15

20

25

30

35

40

45

50

Po

sitio

n [

de

g]

Position

θ

ψ

θd

ψd

(a)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Time [s]

-20

-15

-10

-5

0

5

10

15

20

Inp

ut

Vo

lta

ge

[V

]

Voltages

Vp(t) [V]

Vy(t) [V]

(b)

Figure 6: LQR Simulation (a) Position and (b) Voltage w/ Constant Signal

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Preliminary WorkLQR Simulation

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Time [s]

-100

-50

0

50

Err

or

[de

g]

Error

eθ [deg]eψ [deg]eθ̇[deg/s]

eψ̇[deg/s]

Figure 7: LQR Simulation Error w/ Constant Signal

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Preliminary WorkLQR via USB

0 5 10 15 20 25 30

Time [s]

-15

-10

-5

0

5

10

15

Pitch

[D

eg

]

Pitch Encoder

(a)

0 5 10 15 20 25 30

Time [s]

-20

-15

-10

-5

0

5

10

15

20

Vo

lta

ge

[V

]

Pitch Voltage

(b)

Figure 8: LQR Pitch Position (a) and Voltage (b) on PC with Square Wave Input

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Preliminary WorkLQR via USB

0 5 10 15 20 25 30

Time [s]

-80

-60

-40

-20

0

20

40

60

Ya

w [

De

g]

Yaw Encoder

(a)

0 5 10 15 20 25 30

Time [s]

-20

-15

-10

-5

0

5

10

15

20

Vo

lta

ge

[V

]

Yaw Voltage

(b)

Figure 9: LQR Yaw Position (a) and Voltage (b) on PC with Square Wave Input

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Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Preliminary WorkLQR via Wireless

0 5 10 15 20 25 30

Time [s]

-60

-40

-20

0

20

40

60

Po

sitio

n [

de

g]

(a)

0 5 10 15 20 25 30

Time [s]

-20

-15

-10

-5

0

5

10

15

20

Vo

lta

ge

[V

](b)

Figure 10: Performance in following user’s command (a) tracking pitchangle, and (b) pitch motor input voltage

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Preliminary WorkLQR via Wireless

0 5 10 15 20 25 30

Time [s]

-150

-100

-50

0

50

100

150

Po

sitio

n [

de

g]

(a)

0 5 10 15 20 25 30

Time [s]

-20

-15

-10

-5

0

5

10

15

20

Vo

lta

ge

[V

](b)

Figure 11: Performance in following user’s command (a) tracking yawangle, and (b) yaw motor input voltage.

G. Janiak, K. Vonckx (Bradley University) 2-DOF Helicopter (Proposal) November 29, 2018 27 / 36

http://www.bradley.edu

Outline

1 Introduction

2 Background StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

3 Subsystem Level Functional RequirementsBlock Diagram

4 Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

5 Parts List

6 Schedule for Completion

7 Future Directions

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Demonstration

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Parts List

HardwareTwo Quanser Aeros

Q-flex2 Embedded Panel

Two Single Board Computers (Raspberry Pi 3 Model B)Android Smart-phone or Tablet(Note that Apple devices could also be used, however modifications areneeded)

SoftwareMATLAB & Simulink

Raspberry Pi Support PackageAndroid Support Package

Quanser Real-Time Control (QUARC)

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DeliverablesSchedule for Completion

2018

Sep Oct Nov Dec

66%Research100%Last Years Work

100%LQG

0%ADP

66%Simulation100%LQR

100%LQG

0%ADP

50%Implementation100%LQR USB

100%LQR Raspberry Pi

100%LQR Android

0%LQG USB

0%LQG Raspberry Pi

0%LQG Android

Figure 12: Gantt chart for Fall 2018

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DeliverablesSchedule for Completion

2019

Jan Feb Mar Apr May

0%Implementation0%ADP USB

0%ADP Raspberry Pi

0%ADP Android

0%Testing

Figure 13: Gantt Chart for Spring 2019

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Future Directions

Two more motion control algorithms (LQG & ADP)

Test plan

Implmentation on 6-DOF Helicopter

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Summary

Embedded implementation of control algorithms

Mobile interface

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For Further Reading I

[1] S. I. K. Q. Ahmed, A.I.Bhatti, “2-sliding mode based robust controlfor 2-dof helicopter,” 11th International Workshop on VariableStructure Systems, June 2010.

[2] W. Chang, J. Moon, and H. Lee, “Fuzzy model-based output-trackingcontrol for 2 degree-of-freedom helicopter,” Journal of ElectricalEngineering Technology, vol. 12.00, no. 1, pp. 1921–1928, 2017,quanser product(s): 2 DOF Helicopter. [Online]. Available:http://www.jeet.or.kr/LTKPSWeb/uploadfiles/be/201705/290520170957344003750.pdf

[3] E. Kayacan and M. Khanesar, “Recurrent interval type-2 fuzzy controlof 2-dof helicopter with finite time training algorithm,” inIFAC-PapersOnLine, July 2016, pp. 293–299.

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http://www.bradley.eduhttp://www.jeet.or.kr/LTKPSWeb/uploadfiles/be/201705/290520170957344003750.pdfhttp://www.jeet.or.kr/LTKPSWeb/uploadfiles/be/201705/290520170957344003750.pdf

For Further Reading II

[4] H. B.-P. P. Mndez-Monroy, “Fuzzy control with estimated variablesampling period for non-linear networked control systems: 2-dofhelicopter as case study,” Transactions of the Institute ofMeasurement, vol. no. 7, October 2012.

[5] W. Gao and Z.-P. Jiang, “Data-driven adaptive optimaloutput-feedback control of a 2-dof helicopter,” in American ControlConference, Boston Marriott Copley Place, Boston, MA, USA, July2016.

[6] M. Hernandez-Gonzalez, A. Alanis, and E. Hernandez-Vargas,“Decentralized discrete-time neural control for a quanser 2-dofhelicopter,” Applied Soft Computing, 2012.

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IntroductionBackground StudyControl TechniquesModeling a 2-DOF HelicopterPrior Work

Subsystem Level Functional RequirementsBlock Diagram

Preliminary WorkLQR SimulationLQR via USBLQR via WirelessDemonstration

Parts ListSchedule for CompletionFuture Directions

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