Tài liệu Motion Control Theory Needed in the Implementation of Practical Robotic Systems pptx

v
Table of Contents

(ABSTRACT) ii
(GRANT INFORMATION) ii
ACKNOWLEDGMENTS iii
TABLE OF FIGURES vii
INDEX OF TABLES viii
CHAPTER 1. INTRODUCTION 1
PART I. MOTION CONTROL 2
CHAPTER 2. CHOOSING A MOTION CONTROL TECHNOLOGY 2
Field-Wound versus Permanent Magnet DC Motors 5
Brush or Brushless 6
Other Technology Choices 6
CHAPTER 3. THE STATE OF THE MOTION CONTROL INDUSTRY 8
Velocity Controllers 12
Position Controllers 15
S-curves 17
The No S-curve 21
The Partial S-curve 22
The Full S-curve 24
Results of S-curves 24
CHAPTER 4. THE STATE OF MOTION CONTROL ACADEMIA 26
Motor Modeling, Reference Frames, and State Space 26
Control Methodologies 31
Design of a Sliding Mode Velocity Controller 33
Design of a Sliding Mode Torque Observer 34
A High Gain Observer without Sliding Mode 36
Conclusion 42
CHAPTER 5. SOFT COMPUTING 45
A Novel System and the Proposed Controller 45
The Fuzzy Controller 48
Results and Conclusion 52

vi

CHAPTER 6. A PRACTICAL IMPLEMENTATION 57
Purchasing Considerations 57
Motion Control Chips 59
Other Considerations 61
CHAPTER 7. A CONCLUSION WITH AN EXAMPLE 63
Conclusion 63
ZAPWORLD.COM 63
PART II. AUTOMATED NAVIGATION 66
CHAPTER 8. INTRODUCTION TO NAVIGATION SYSTEMS 66
CHAPTER 9. IMAGE PROCESSING TECHNIQUES 69
CHAPTER 10. A NOVEL NAVIGATION TECHNIQUE 71
CHAPTER 11. CONCLUSION 77
VITA 78
BIBLIOGRAPHY 79
References for Part I 79
References for Part II 82

vii
Table of Figures

Figure 2.1. A typical robotic vehicle drive system. 2
Figure 2.2a. DC Brush Motor System 4
Figure 2.2b. DC Brushless Motor System 4
Figure 2.3a. Field-Wound DC Brush Motor. 2.3b. Torque-Speed Curves. 5
Figure 3.1. Common representations of the standard DC motor model. 8
Figure 3.2. A torque-speed plotting program 10
Figure 3.3. Bode Diagram of a motor with a PI current controller 10
Figure 3.4. A typical commercial PID velocity controller 12
Figure 3.5a. A step change in velocity. 3.5b. The best response 14
Figure 3.6a. A popular position compensator 16
Figure 3.6b. A popular position compensator in wide industrial use 16
Figure 3.6c. A popular position compensator 16
Figure 3.7. Two different points of view of ideal velocity response. 18
Figure 3.8. S-curves profiles resulting in the same velocity 19
Figure 3.9. S-curve profiles that reach the same velocity and return to rest 20
Figure 3.10. S-curve profiles that reach the same position 25
Figure 4.1. The stationary and the rotating reference frame 28
Figure 4.2. Three models of friction 30
Figure 4.3. Block diagram of system to be observer and better controlled 32
Figure 4.4. Comparison of High Gain and Sliding Mode Observers 37
Figure 4.5. Block diagram of a system with a sliding mode observer and
feedforward current compensation 38
Figure 4.6. Comparison of three control strategies (J=1 p.u.) 39
Figure 4.7. Comparison of three control strategies (J=2 p.u.) 41
Figure 4.8. Comparison of three control strategies (J=10 p.u.) 41
Figure 5.1. An inverted pendulum of a disk 45
Figure 5.2. Inverted Pendulum on a disk and its control system. 48
Figure 5.3. Input and Output Membership Functions 50
Figure 5.4. This surface maps the input/output behavior of the controller 50
Figure 5.5. The final shape used to calculate the output and its centroid 52
Figure 5.6. The pendulum and disk response to a 10° disturbance 54
Figure 5.7. The pendulum and disk response to a 25° disturbance 55
Figure 5.8. The pendulum and disk response to a 45° disturbance 56
Figure 6.1. Voltage captures during two quick motor stall current surges 61
Figure 7.1. The ZAP Electricruizer (left) and Lectra Motorbike (right) 64
Figure 8.1. A typical autonomous vehicle system 66
Figure 10.1. The Mexican Hat 71
Figure 10.2. The Shark Fin 72
Figure 10.3. A map of obstacles and line segments 73
Figure 10.4. The potential field created by Mexican Hat Navigation 73
Figure 10.5. The path of least resistance through the potential field 74
Figure 10.6. The resulting path through the course 74

viii
Index of Tables


T
ABLE
3.2. F
EEDBACK PARAMETERS TYPICALLY AVAILABLE FROM MOTOR CONTROLLERS
AND THEIR SOURCES
11
T
ABLE
4.1. T
RANSFORMATIONS BETWEEN DIFFERENT DOMAINS ARE POSSIBLE
28
T
ABLE
5.1.

W
EIGHT
G
IVEN TO
PID C
ONTROLLERS
T
ORQUE
C
OMMAND
49
T
ABLE
5.2.

W
EIGHT
G
IVEN TO
PID C
ONTROLLERS
T
ORQUE
C
OMMAND
51
T
ABLE
6.1. M
OTION
C
ONTROL
C
HIPS AND
P
RICES
59
T
ABLE
6.2. T
OP
10 T
IME
C
ONSUMING
T
ASKS IN THE
D
ESIGN OF
A
UTONOMOUS
E
LECTRIC
V
EHICLES
62
Chapter 1 Introduction
1
Chapter 1. Introduction

Most research in robotics centers on the control and equations of motion for
multiple link and multiple degree-of-freedom armed, legged, or propelled systems. A
great amount of effort is expended to plot exacting paths for systems built from
commercially available motors and motor controllers. Deficiencies in component and
subsystem performance are often undetected until the device is well past the initial design
stage.
Another popular area of research is navigation through a world of known objects
to a specified goal. An often overlooked research area is the navigation through an area
without a goal, such as local obstacles avoidance on the way to a global goal. The
exception is smart highway systems, where there is a lot of research in lane and line
tracking. However, more general applications such as off-road and marine navigation
usually rely on less reliable methods such as potential field navigation.
Part I presents the research necessary for the robotics designer to select the motor
control component and develop the control system that will work for each actuator. It
follows the path the robot developer must follow. Hardware and performance constraints
will dictate the selection of the motor type. With this understanding environmental and
load uncertainty will determine the appropriate control scheme. After the limitations of
the available control schemes are understood the hardware choices must be revisited and
two compromises must be made: feedback quality v system cost and response v power
budget.
Part II presents the research necessary to develop a practical navigation system for
an autonomous robotic vehicle. The most popular sensors and hardware are surveyed so
that a designer can choose the appropriate information to gather from the world. The
usual navigation strategies are discussed and a robust novel obstacle detection scheme
based on the Laplacian of Gaussians is suggested as robust obstacle avoidance system.
Designers must take this new knowledge of navigation strategies and once again return to
the choice of hardware until they converge upon an acceptable system design.
Chapter 2 Choosing a Motion Control Technology
2
Part I. Motion Control

Chapter 2. Choosing a Motion Control Technology













Figure 2.1. A typical robotic vehicle drive system showing the parts discussed here.

Many robots are built and operated only in simulation. Regardless of how
painstakingly these simulations are designed it is rare that a device can be constructed
with behavior exactly matching the simulation. The construction experience is necessary
to be assured of a practical and robust mechanical and electrical design. With an
advanced or completed prototype the mechanical designer can provide all the drawings,
inertias, frictions and losses to create an accurate simulation. Ideally, the choice of motor,
motor controller, feedback devices and interface is made and developed concurrently
with the system design. This chapter serves a guide to the appropriate technology.
Battery

Battery

Motor

Driver

GEARS

WHEELS

Motor

Motor

Controller

Feedback

Topics Covered Here

Chapter 2 Choosing a Motion Control Technology
3

Table 2.1 presents each of the popular motor types and their most important
characteristics for the purpose of constructing robotic vehicles. An important factor that
has been left out of the table is cost. There are some good reasons for doing this:
• Competition has made the cost for a given performance specification relatively
invariant across the available appropriate technologies.
• The cost of powering, controlling, and physically designing in the motion system
with the rest of the robot is greatly reduced by choosing the appropriate motor.

Table 2.1. Common motor types and their characteristics
Motor Type Power at
Motor Leads
Typical
Efficiency
(1)

Coupling Controller
DC Brush DC < 50% Direct or
Reducer
Simple to
Complex
DC Brushless Variable Freq.
3 Phase AC
> 90% Direct or
Reducer
Complex
AC Induction 3 Phase AC < 90% Reducer Simple
AC Synchronous Variable Freq.
3 Phase AC
> 90% Direct or
Reducer
Simple to
Complex
Stepper Digital Pulse < 5% Direct or
Reducer
Simple
(1) Efficiencies are for motors below 3.7 kW. By necessity, motor efficiency increases with size for all
types and is over 90% for almost all motors in the tens of kilowatts.

The first consideration in choosing a motor type is the input power available.
Large stationary robots used in automation and manufacturing can assume a 3 Phase AC
supply, but robotic vehicles are often all-electric and operate off DC busses or hybrid
electric and convert power to a common DC bus. Figure 2.2 illustrates how DC motors
are named “DC” based on the input power to the controller, not the shape of the voltage
or current on the motor leads.
Chapter 2 Choosing a Motion Control Technology
4





Figure 2.2a. DC Brush Motor System with inverter (left), DC on motor leads (center), and brush motor.





Figure 2.2b. DC Brushless Motor System with inverter (left), AC on motor leads (center), and brushless motor.

The remainder of this thesis will concentrate on DC motors as they are the most
common choice for electrically powered robotic vehicles. However, it is noteworthy that
for large vehicles and power levels over about 5 kW, an inverter controlled AC machine
may be a better choice because of its availability in larger size ranges and the greater
control over the motor’s torque-speed characteristics gained by using windings to
generate all the fluxes instead of relying on permanent magnets. Luttrell et. al. [1] used a
synchronous motor that is inverter-fed off a DC bus in the award-winning Virginia Tech
1999 Hybrid Electric FutureCar.
AC Induction motors are rarely used in propulsion because they slip, and
therefore lose efficiency, whenever they are under load and also have very poor
performance at low speed, again where slip is high. However, AC Induction motors are
the general work-horse of industry because of relatively high starting torque and high
general reliability. There are several attempts to encourage the research and industry-
wide adoption of high-efficiency induction motors, such as the specifications of Pyrhönen
et. al. in [4].

V+
V-

V+
V-

V+
V-

V+
V-

V+
V-
5
0

5



0

5

Chapter 2 Choosing a Motion Control Technology
5
Stepper motors are built to “step” from one position to the next through a fixed
angle of rotation every time they receive a digital pulse. The common fixed angles sold
by Oriental Motor in [2] are 0.72° and 1.8°, or 500 and 200 steps per revolution. Stepper
motors are appealing in many applications where easy control and smooth velocity and
position changes are not required. A common example of an easy to control and low cost
application is a stepper motor used to turn the helical snack dispensing screw in a
vending machine. Sometimes the discrete motion of a stepper motor is advantageous, as
when a stepper motor and belt drive is used to step a horizontal document scanner
vertically down a document. Robots and electric vehicles are often covered with sensors
and parts that are best moved with stepper motors, but their jerky motion and low
efficiency make them a poor choice for vehicle propulsion.
Field-Wound versus Permanent Magnet DC Motors

DC Brush motors all use brushes to transfer power to the rotor. However, the field
may be created by permanent magnets or by another set of windings. When another set of
windings is used De La Ree [3] shows how the two sets of motor leads can be connected
in different arrangements to produce different torque-speed curves, as shown in Figure
2.3b.

Figure 2.3a (left). Field-Wound DC Brush Motor. 2.3b. Torque-Speed Curves for various configurations.
Chapter 2 Choosing a Motion Control Technology
6
In general wound field DC motors are bigger, bulkier, and less efficient than
permanent magnet DC machines. Their use in electric vehicles should be compared to the
use of AC synchronous machines. The following chapters will further limit discussion to
permanent magnet DC brush motors. DC brushless motors always use windings in the
stator and permanent magnets on the rotor to remove the need for brushes.

Brush or Brushless

Brush motors are older and more broadly used. They have difficulty at high speed
when brush currents start arcing from pad to pad. They have problems with torque ripple
at low speed when high amounts of current and flux switch from one winding to the next.
Brushes create sparks that may need to be contained and the brushes will eventually
wear. However, brush motors are easy to control, and the motor leads can be connected
directly to a DC current source.
Brushless motors overcome all the problems of brush motors. They work at very
high speeds even speeds where air or magnetic bearings are required because ball
bearing liquefy. They can be designed to work at low speed with very high torque and
low torque ripple. The trade-off comes in the complexity of the controller. The brushless
controller needs to modulate three sinusoidal signals in-phase with the electrical or
mechanical angle of the machine. The deciding factor that makes the choice of brushless
motors worthwhile is if designs allow for direct drive. Brushless motors are more likely
to be available with torque-speed characteristics that allow them to be directly coupled to
the load, avoiding the cost, size, and loss of a reducer like a gearbox.

Other Technology Choices

Brush and Brushless motors are both available framed the typical motor with
bearings in a housing with shaft and wire leads coming out and frameless the rotor,
stator, and slip-ring or brush assembly (if a brush motor) come as loose pieces and are

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