generating intelligent commands to control mechatronic devices william singhose

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Generating Intelligent Commands to Control Mechatronic Devices William Singhose

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Page 1: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Generating Intelligent Commands to Control Mechatronic Devices

William Singhose

Page 2: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

What is Control?

PhysicalPlant

ControlEffort Response

Getting the System to do What you Want

Page 3: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Add a Feedback Loop

PhysicalPlant

FeedbackControllerΣReference Control

Effort Response

-+Response

PhysicalPlant

FeedbackControllerΣ

Reference ControlEffort Response

-+ResponsePhysical

PlantΣReference

ControlEffort Response

-+FeedbackController

Response

Page 4: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Simple Control Systems

PhysicalPlant

ControlEffort Response

PhysicalPlant

ControlEffort ResponseCommand

Generator

DesiredPerformance

Page 5: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

PhysicalPlant

FeedbackController

CommandGenerator

FeedforwardController

ΣΣ

ControlEffort

Reference

Reference

ResponseDesired

Performance

General Control System

Page 6: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Landmine Detecting Robot

Page 7: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

QuickTime™ and a decompressor

are needed to see this picture.

Page 8: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Bridge Crane

QuickTime™ and aMotion JPEG OpenDML decompressor

are needed to see this picture.

Page 9: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Bridge Crane Problem(and solution)

θ

T r o l l e y

C a b l e

P a y l o a d

g

x

0

1

2

3

4

5

6

7

8

0 5 10 15

Trolley

Payload

Position

Time

Button On

0

1

2

3

4

5

6

7

8

0 5 10 15

Trolley

Payload

Position

Time

Button On

Page 10: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Why is Vibration Cancelled?

-0.4

-0.2

0

0.2

0.4

0.6

0 0.5 1 1.5 2 2.5 3

A1 ResponseA2 ResponseTotal Response

Position

Time

A1

A2

Page 11: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Simple Derivation

V ω,ζ( ) =e−ζωtn C ω,ζ( )[ ]2

+ Sω,ζ( )[ ]2

C ω,ζ( ) = Aieζωti cosωdti( )

i=1

n

S ω,ζ( ) = Aieζωti sinωdti( )

i=1

n

Constraints

VibrationAmplitude

Ai =1∑Normalization

Ai >0 i =1,...,nPositive Impulses

t1 =0Time Optimality

Page 12: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

0 = Aieζωti cosωdti( )

i=1

n

∑ =A1eζωt1 cosωdt1( )+A2e

ζωt2 cosωdt2( )

0 = Aieζωti sinωdti( )

i=1

n

∑ =A1eζωt1sinωdt1( )+A2e

ζωt2 sinωdt2( )

0=A1 +A2eζωt2 cosωdt2( )

0=A2eζωt2 sinωdt2( )

ωdt2 =nπ, n=1,2,...

t2 =nπωd

=nTd2

, n=1,2,...

Simple Derivation(V=0, 2 impulses)

A1A2

t1 t2

0=A1 − 1−A1( )e

ζπ

1−ζ2

⎜ ⎜ ⎜

⎟ ⎟ ⎟

A1 =e

ζπ

1−ζ2

⎜ ⎜ ⎜

⎟ ⎟ ⎟

1+e

ζπ

1−ζ2

⎜ ⎜ ⎜

⎟ ⎟ ⎟

t2 =Td2

Aiti

⎣ ⎢

⎦ ⎥ =

11+K

K1+K

0 0.5Td

⎣ ⎢ ⎢

⎦ ⎥ ⎥

K =e

−ζπ

1−ζ2

⎜ ⎜ ⎜

⎟ ⎟ ⎟

Page 13: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Input Shaping Arbitrary Commands

Page 14: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

QuickTime™ and aH.264 decompressor

are needed to see this picture.

Page 15: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Typical Responses

Page 16: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

QuickTime™ and a decompressor

are needed to see this picture.

Page 17: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

10-Ton Industrial Bridge Crane

• 6mx5mx40m

• Interfaces: Pendent, Joystick, Touchscreen, Wireless

• Overhead Camera

Page 18: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

0

1

2

3

4

0 10 20 30 40 50

Bridge Position

Hook Position

Position (in)

Time (sec)

Input Shaping and Feedback Control:Experimental Data

Disturbance at End

0

1

2

3

4

0 5 10 15 20 25 30 35

Bridge Position

Payload Position

Position (in)

Time (sec)

Disturbance During Motion

Page 19: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Concurrent DesignWith Feedback Control

PlantController

Sensors

ΣCommandGenerator

Page 20: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Current Design of PD Feedback And Command Shaping

0

0.5

1

0 0.2 0.4 0.6 0.8 1

PD

PD+Shaping

5% Settling Time, s

Damping Ratio (ζ)

0.39

0.15

Page 21: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Human Operator Studies

LongShort

End

Start

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12 13

ShapedUnshaped

Time (sec)

Operator Number

Page 22: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Human Operator Learning

0

50

100

150

200

250

300

0 2 4 6 8 10

Unshaped

Shaped

Completion Time (sec)

Trial Number

Page 23: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Human Operator Learning

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9

Completion Time (sec)

Trial Number

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9

Completion Time (sec)

Trial Number

Unshaped Shaped

Page 24: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Portable Tower Crane

• 2mx2mx340o

• Interfaces: Pendent, GUI, Internet GUI

• Overhead Camera

• Used by Researchers and Students in Atlanta, Japan, Korea

Page 25: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Tower Crane: System Overview

Screen Interface

P a y lo a d

Tr o ll e y

P L C D r iv e s

A C - A C

T o w e r C r a n eM o to r

C a m e r a

L i m i t s

P CIn t e r n e t

A t la n t a

J A P A N

A n yw h e r e

E n c o d e r

P C

*

Page 26: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Other Applications• Many types of cranes

• Disk drives

• Long reach robots

• Coordinate measuring machines

• Milling machines

• Spacecraft

xy

z

Touch-TriggerProbe

MeasuredPart

Page 27: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

• Scale of Micro Meters (10-6m)

• High Spindle Speeds (120 kRPM)

Application of Command Shapingto Micro Mills

Page 28: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

Page 29: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Experimental Results

-0.02

-0.01

0

0.01

0.02

10 11 12 13 14 15

UnshapedShaped

Y Position (mm)

X Position (mm)

Stage Tracking Error

-0.02

-0.01

0

0.01

0.02

10 11 12 13 14 15

UnshapedShaped

Y Position (mm)

X Position (mm)

36 μm

15 μm

Part Surface

Page 30: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

xy

z

Touch-TriggerProbe

MeasuredPart

Coordinate Measuring Machines

Page 31: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

-60

-40

-20

0.0

20

40

60

0.40 0.60 0.80 1.00 1.20

Shaped Deflection

Unshaped Deflection

Deflection (Laser-Encoder) (

μ )m

( )Time sec

- Pre Hit Region

Coordinate Measuring Machine (CMM) Deflection

Page 32: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Disk Drive Head TesterCapacitance Gage

Piezo Actuator

x stage

y stage

Drive Head Holder

Unshaped

-50

0

50

100

150

200

250

-100

-50

0

50

100

150

200

0 0.01 0.02 0.03 0.04 0.05 0.06

Unshaped Response (

μ)in

(Shaped Response

μ)in

( )Time sec

Shaped

Page 33: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Painting Robot

.

RecordingSurface

AirBrush

X

Y

Simulated Response(Scaled Down)

Desired Response

Directionof Travel

Simulated Response(Scaled Down)

Desired Response

Directionof Travel

Desired Response

Desired Response

Page 34: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Space Robot

Page 35: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Spacecraft Control

umbilical secondary gimbalprimary gimbal

reaction wheels

Page 36: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

umbilical secondary gimbalprimary gimbal

reaction wheels

MACE Space Shuttle Endeavor, 1995

Page 37: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

MACE Space Shuttle Endeavor, 1995

-1.5

-1

-0.5

0

0.5

1

1.5

0 1 2 3 4 5 6 7 8

Unshaped Step

2-Hump EI ShapedGimbal Position (degrees)

Time (sec)

Page 38: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Input Shaping with On-Off Actuators

Page 39: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

How Can We UseInput Shaping on On/Off Actuators?

0 0 Δ

* Initial Command Input Shaper

0 Δ

Shaped Command

D

+D Δ

Not On/Off

Page 40: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Flexible Satellites(Tokyo Institute of Technology)

Page 41: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Time Optimal Control(Special Input Shaper)

0

0.5

1.0

-0.5

-1.0

Shaped Input

12

1

-2 -2Unshaped Input

Input Shaper

0

0.5

1.0

*

Variables: 1) Impulse Times

Page 42: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Fuel-Efficient Input Shaping

Time-Optimal

Fuel-Efficient

-u max

u max

t1

t2

t3

t4

t5

*1

-2 -2

2

1

t1

t2

t3

t4

t5

umax

-u max

u max

t1

t2

t3

t4

t5

t6

t7

t8

*1

-1 -1

11 1

-1 -1

t1

t2

t3

t5

t4

t6

t7

t8

umax

Page 43: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Comparison of Maneuver Times

4

6

8

10

12

14

16

18

0 5 10 15 20 25 30 35 40

Time-Optimal ProfilesFuel-Efficient Profiles

Move Duration (sec.)

Slew Distance

Page 44: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Comparison of Fuel Usage

0

5

10

15

20

0 5 10 15 20 25 30 35 40

Time-Optimal

Fuel Efficient

Fuel Usage (sec.)

Slew Distance

Wasted Fuel

Page 45: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Transient Deflection with On-Off Shaping

-1

0

1

2

3

4

5

0 2 4 6 8 10 12

Mass CenterDeflection (x 2-x 1)

Response

Time (sec)

m2m1

Too Large?

Page 46: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Deflection Sampling

-0.5

0

0.5

0 2 4 6 8 10

Percentage Deflection, D(t)/D

max

Time (sec)

Limit the Deflection at Specific Times

Deflection May Exceed Limit Between Deflection Sampling Points

DL

-D L

Page 47: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Simulation Results(Slew Distance = 5 units)

m2m1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

0 5 10 15

Fuel-Efficient80% Limited60% Limited20% Limited

Deflection, x

2-x

1

Time (sec)

Page 48: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Slew Duration vs. Deflection Limit(Slew Distance = 5 units)

0

5

10

15

20

25

0.0 0.2 0.4 0.6 0.8 1.0

Slew Duration (sec)

Percentage Deflection

Page 49: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

QuickTime™ and aMotion JPEG OpenDML decompressor

are needed to see this picture.

Page 50: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

Endpoint Deflection

-40

-20

0

20

40

0 1 2 3 4 5 6

Bang-Bang

ZV FE-FE-FE

ZVD FE-FE-FE

Endpoint Deflection (mm)

Time (sec)

Page 51: Generating Intelligent Commands to Control Mechatronic Devices William Singhose

• The Command Used toDrive a Machine is ofFundamental Importance

• Unwanted Motion can beDangerous & Costly

• Oscillation Can Be Reduced Quickly and Easily by Command

Shaping

• Command Shaping is the EASIEST Control Method

Conclusions

Page 52: Generating Intelligent Commands to Control Mechatronic Devices William Singhose