Knowledge-Based Control with Application to Robots

206 Pages·1989·2.93 MB·English

by  Dr. Clarence W. de Silva, Professor Alistair G. J. MacFarlane (eds.)

Lecture Notes ni
Control and
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C.W. de Silva
.A .G .J MacFarlane
Knowledge-Based Control
with Application to Robots
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Series Editors
M. Thoma • A. Wyner
Advisory Board
.L D. Davisson • A. G. .J MacFarlane • H. Kwakernaak
.3 L Massey • Ya Z. Tsypkin • A. .J Viterbi
Authors
Dr. Clarence W. de Silva
NSERC Professor of Industrial Automation
Department of Mechanical Engineering
University of British Columbia
Vancouver, B.C. V6T 1W5
CANADA
Professor Alistair G. J. MacFarlane
Principal and Vice-Chancellor
Heriot-Watt University
Riccarton, Edinburgh EH 14 4AS
SCOTLAND, U.K.
ISBN 3-540-51143-1 Springer-Verlag Berlin Heidelberg New York
ISBN 0-387-51143-1 Springer-Verlag New York Berlin Heidelberg
Library of Congress Cataloging in Publication Data
De Silva, Clarence .W
Knowledge-based control with application to robots /C.W. de Silva, A.G.J. MacFarlane.
(Lecture notes in control and information sciences ; 123)
ISBN 0-387-51143-1 (U.S.)
t. Robots--Control systems.
2. Intelligent control systems.
3. Expert systems (Computer science).
I. MacFarlane, A.G.J. (Alistair George James), .II Title. III. Series.
TJ 21t.35.D42 1989
629.8'92--dc20 89-10088
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PREFACE
The work presented here considers the integration of knowledge-
based soft control with hard control algorithms. As a specific application,
the development of a knowledge-based controller for robotic manipulators
is addressed. Servo control alone is known to be inadequate for nonlinear
and high-speed processes including robots. Furthermore, knowledge-based
control such as fuzzy control, when directly included in the servo loop, has
produced unsatisfactory performance in research robots. These
considerations, along with the fact that human experts can very
effectively perform tuning functions in process controllers, form the basis
for the control structure proposed in this work.
The proposed control structure consists of a three-level hierarchy.
The lowest level has a set of PID controllers closed around a high-speed
decoupling and linearising controller. A recursive algorithm has been
developed for implementation of this nonlinear feedback controller. The
second level contains a set of knowledge-based controllers known as servo
experts. There is one servo expert for each degree of freedom of the
process. A servo expert is a knowledge system of the forward production
type. It monitors the corresponding process response and makes inferences
on the basis of a set of performance specifications. These inferences are
supplied to the fuzzy controller at Level 3. The knowledge base of the
fuzzy controller consists of expert knowledge in the form of linguistic
rules for servo tuning. These rules are expressed as fuzzy decision tables
by using membership functions of the condition and action variables, fuzzy
logic, and the compositional rule of inference. This knowledge, along with
external sensory data and other available information, is used to arrive at
tuning decisions for the PID controllers. Control specifications,
parameters of the decoupling controller, and the rule bases themselves can
be modified as well, using this type of knowledge, at the fuzzy control
level. Separation of the knowledge-based control into two levels, with the
lower level functioning as an intelligent preprocessor and the upper level
containing a fuzzy knowledge base that is representative of expert
knowledge in servo tuning, is an important characteristic of the proposed
control structure.
IV
The background work presented includes a thorough literature review
of hard algorithmic control and knowledge-based soft control of robotic
manipulators. Theory, concepts, and procedures for developing each level in
the proposed hierarchical control structure, have been established.
As an application of the proposed control structure, a
knowledge-based control system has been developed for a
two-degree-of-freedom robot. The system contains a servo expert for each
joint of the robot, developed using a commercially available AI toolkit
(MUSE). The unstructured code in the servo experts was written ni PopTalk
language and the structured code was developed using the editor_tool
facility of MUSE. The fuzzy controller was developed off line and it has
been implemented as a set of decision tables. A robot simulator was
developed as a separate UNIX process written in C language. The simulator
has been interfaced with the servo experts and with the fuzzy controller
using the UNIX Socket facility, and the Channel objects and Data Stream
objects that are available with the AI toolkit. Data channel programs were
written in PopTalk. Performance of the overall system was evaluted using
simulation experiments.
Simulation experiments which were carried out included single-joint
tests with step, ramp, and sine inputs. Results have demonstrated the
superiority of the proposed control approach in comparison with
conventional control without knowledge-based tuning. Simulations of a
series of seam tracking tasks were carried out with the complete robot.
Initial position errors were introduced and acceleration disturbances were
injected during operation, to represent various situations such as
pick-and-place operations, fast negotiation of a corner, and operation
under an imperfect nonlinear feedback controller. In each simulation,
superior results were achieved with the proposed controller, in comparison
to a conventional controller. Even though the performance generally
improved with the bandwidth of the knowledge-based controller, a
bandwidth of at least an order of magnitude smaller than the servo
bandwidth consistently provided good performance.The controller was also
found to be robust in the sense of having relative insensitivity to initial
values, and other parameter values of the controller.
v
The monograph is divided into seven chapters. Chapter 1 presents the
background and the scope of the material given in the remaining six
chapters. Chapter 2 reviews the kinematic and kinetic formulation of
robots, giving particular consideration to recursive algorithms for
computed torque/force control. This material forms the foundation for the
recursive algorithm developed ni Chapter 4 for linearising and decoupling
control of robots, and is an important part ni the development of the
lowest level of the proposed control structure. Fuzzy logic is used in the
development of the top level of the control structure. Chapter 3 gives a
simplified review of fuzzy logic and fuzzy control, with geometric
illustrations and examples. Chapter 4 presents a general description of the
proposed control structure. Chapter 5 describes the application of the
knowledge-based control structure to robotic manipulators. The operation
of the system developed ni Chapter 5 is described ni Chapter .6 Simulation
experiments are described and representative results are discussed. The
computer programs used in this application are listed in Appendix t.
Important features of the proposed control structure are highlighted ni
Chapter 7, and directions are indicated for further developments. A
bibliography of related work is given under References, at the end of the
monograph.
This monograph is suitable for students, researchers, and practising
professionals ni the fields of Automatic Control and Robotics. The material
is presented in simple and clear language with sufficient introductory
information. Someone with na undergraduate knowledge ni dynamics and
control should be able ot esu this book without any difficulty.
Engineering Department .C .W de S dna .A .J .G M
University of Cambridge
ACKNOWLEDGMENTS
We are grateful to Dr. .D J. Williams for encouraging this work and for
providing computing facilities. C. W. de Silva wishes to extend his thanks
to the Fulbright Commission for the fellowship which, in part, supported
this work. The facilities provided by the Engineering Department of the
Cambridge University are gratefully acknowledged.
C. W. de Silva, with the endorsement of
Professor A. G. J. MacFarlane,
wishes to dedicate this work to
his mother and to the memory of his father.
TABLE OF CONTENTS
BACKGROUND
.
1.1 Introduction ................................................ 1
1.2 Objectives ................................................. 3
1,3 Robot Charactedsation ....................................... 4
Classification ............................................ 5
Operation and Control .................................... 7
1.4 Robot Dynamics ............................................ 9
Inverse Kinematics ...................................... 10
Inverse Dynamics (Recursive Formulation) ................... 13
Friction and Backlash .................................... 14
1.5 Control of Robots .......................................... 17
1.6 Knowledge-Based Control ................................... 24
Knowledge Representation ................................ 26
Fuzzy Knowledge ........................................ 30
Fuzzy Control ........................................... 32
. DYNAMIC FORMULATION OF ROBOT BEHAVIOUR
2,1 Introduction ............................................... 40
2.2 Kinematic Formulation ...................................... 40
Homogeneous Transformation ............................. 41
The Denavit-Hartenberg Notation .......................... 46
Inverse Kinematics ...................................... 49
Differential Kinematics .................................... 50
VIII
2.3 Inverse Dynamics .......................................... 53
Recursive Formulation .................................... 55
FUZZY LOGIC
.
3.1 Introduction ............................................... 57
3.2 Fuzzy Sets ................................................ 57
Membership Function .................................... 59
Symbolic Representation .................................. 59
Examples .............................................. 61
3.3 Logical Operations ......................................... 62
Complement (NOT) ...................................... 62
Union (OR) ............................................. 62
Intersection (AND) ....................................... 63
Implication (IF-THEN) .................................... 63
3.4 Fuzzy Relations ............................................ 64
Cartesian Product of Fuzzy Sets ........................... 66
Extension Principle ...................................... 68
3.5 Fuzzy Dynamic Systems ..................................... 71
3.6 Composition and Inference .................................. 72
Projection .............................................. 72
Cylindrical Extension ..................................... 73
Join ................................................... 74
Composition ............................................ 76
Composition Rule of Inference ............................. 77
IX
3.7 Membership Function Estimation .............................. 80
Averaged Guess Method ................................. 81
Distance Function Method ................................ 81
An Intuitive Relation ...................................... 81
Use of Binary Polling ..................................... 82
Relative Preference Method ............................... 82
. CONTROL STRUCTURE
4.1 Introduction ............................................... 84
4.2 The Control Hierarchy ...................................... 85
4.3 Decoupling and Servo Level ................................. 87
4.4 A Recursive Algorithm ...................................... 94
4.5 Servo Expert Level ......................................... 98
4.6 Fuzzy Control Level ....................................... 101
. SYSTEM DEVELOPMENT
5.1 Introduction .............................................. 104
5.2 Servo Experts ............................................ 105
The MUSE AI Toolkit ................................... 105
Servo Expert Development ............................... 111
5.3 Robot Simulator ........................................... 116
Inverse Kinematics ..................................... 118
5.4 Fuzzy Controller ........................................... 121
X
PERFORMANCE EVALUATION
.
8.1 Introduction .............................................. 134
6.2 Typical Operation ......................................... 135
6.3 Single Joint Experiments ................................... 137
6.4 Seam Tracking Experiments ................................ 143
6.5 Performance and Limitations ................................ 158
. CONCLUSIONS
7.1 Introduction .............................................. 162
7.2 Significance .............................................. 162
7.3 Contributions ............................................. 166
7.4 Future Developments ...................................... 168
REFERENCES ........................................................ 170
APPENDIX 1. PROGRAM LISTING ....................................... 179