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This collection of twenty-three timely contributions covers a
well-selected repertory of topics within the autonomous systems
field. The book discusses a range of design, construction, control,
and operation problems along with a multiplicity of
well-established and novel solutions.
In racent years the LSI technology has witnessed a revoluti onary
development, and allowed substantial reductions in the size and
cost of digital logic circuitry. Computer system building blocks
have progressed from the level of discrete components to the level
of complex ICs involving many logic circuits on a single "chip."
The invention and wide applica tions of microprocessors have
changed the philosophy of the signal processing, measurement and
control engineering fields. The microprocessor-based digital signal
processing systems and controllers have replaced the conventional
ones based on standard analog and digital computing equipment. The
first microprocessors and "on-chip" computers have appeared towards
the end of 71 beginning 72. Their evolution since then and the
number of applications, in which they have been utilized, have both
been extremely spectacular. New system concepts and
hardware/software tools are steadily under development to sup port
the microprocessor in its multiple and complex tasks. The goal of
this book is to provide a cohesive and well-balan ced set of
contributions dealing with important aspects and applications of
microprocessors to signal processing, measu rement and system
control. The majority of contributions in clude sufficient review
material and present rather complete treatments of the respective
topics."
The field of Intelligent Systems has expanded enormously during the
last two decades with many theoretical and practical results
already available, which are the outcome of the synergetic merging
of classical fields such as system theory, artificial intelligence,
information theory, soft computing, operations research, linguistic
theory and others. This book presents a collection of timely
contributions that cover a wide, well-selected range of topics
within the field. The book contains forty-seven contributions with
an emphasis on computational and processing issues. The book is
structured in four parts, as follows: Part I: Computer-aided
intelligent systems and tools; Part II: Information extraction from
texts, natural language interfaces and intelligent retrieval
systems; Part III: Image processing and video-based systems; Part
IV: Applications Particular topics treated include: planning;
problem solving; information extraction from texts; natural
language interfaces; audio retrieval systems; multi-agent systems;
image compression, image and segmentation, and human face
recognition. Applications include: peri-urban road network
extraction; analysis of structures; climatic sensor signal
analysis; aortic pressure assessment; hospital laboratory planning;
fatigue analysis using electromyographic signals; forecasting in
power systems. The book can serve as a reference pool of knowledge
that may inspire and motivate researchers and practitioners for
further developments and modern-day applications. The teacher and
student in related postgraduate and research programs can thereby
save considerable time in searching the scattered literature in the
field.
Robotic and manufacturing systems have gained increasing attention
at both the academic and industrial levels. A key component in
their development is the microprocessor, which offers increased
functional capabilities at reduced costs. Microprocessors in
Robotic and Manufacturing Systems provides a balanced,
state-of-the-art presentation of the involvement of microprocessors
in the design and operation of modern robotic and manufacturing
systems. Prepared by a distinguished team of experts, the book
covers a wide repertory of topics, including the latest
developments in the field together with fresh, original results
derived by the contributors. The book provides a unique, cohesive
reference source providing access to the most current advances in
the microprocessor-based robotics and manufacturing field. A subset
of the topics covered is the following: Computation of Robot
Dynamics by Multiprocessor Schemes; Numerical Applications of
Digital Signal Processors in Robotic Computations; Automatic
Scheduling of the Newton-Euler Inverse Dynamics;
Microprocessor-Based Controllers for Robotic Manipulators; Design
Aspects of a Robot Coordinated by a Desktop Computer; Collision
Strategies for Robotic Retreat and Resistance: Microprocessor Based
Implementations; Microprocessor Based Intelligent Welding Systems;
Microprocessors in Robotic/Machine Vison Computer-controlled
Integrated Manufacturing Systems; Microcomputer Expert System Tools
for Robotic and Manufacturing Operations. The reader can save
considerable time in searching the scattered technical information
on the application of microprocessors to industrial robots and
flexible manufacturing systems. The professional can have
readilyavailable a rich set of important analysis, design and
operational results.
Robotics is a modern interdisciplinary field that has emerged from
the marriage of computerized numerical control and remote
manipulation. Today's robotic systems have intelligence features,
and are able to perform dexterous and intelligent human-like
actions through appropriate combination of learning, perception,
planning, decision making and control. This book presents advanced
concepts, techniques and applications reflecting the experience of
a wide group of specialists in the field. Topics include:
kinematics, dynamics, path planning and tracking, control, mobile
robotics, navigation, robot programming, and sophisticated
applications in the manufacturing, medical, and other areas.
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System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches - Volume 2 Knowledge-Based and Fault-Tolerant Techniques Proceedings of the First European Workshop on Fault Diagnostics, Reliability and Related Knowledge-Based Approaches, Island of Rhodes, Greece, August 31-September 3, 1986 (Hardcover, 1987 ed.)
S.G. Tzafestas, Madan Singh, Gunther Schmidt
|
R5,690
Discovery Miles 56 900
|
Ships in 10 - 15 working days
|
This 2-volume work represents the proceedings of the First European
Workshop on Fault Diagnostics, Reliability and Re- lated
Knowledge-Based Approaches held in the Island of Rho- des, Greece
(August 3l-September 3, 1986). This Workshop was organized in the
framework of a joint research project spon- sored by the Commission
of the European Communi ties under the Stimulation Action
Programme. The principal aim of the Workshop was to bring together
people working on the numeric and symbolic (knowledge-based)
treatment of reliability and fault diagnosis problems, in order to
promote the interaction and exhange of ideas, expe- riences and
results in this area. The workshop was a real success, with SS
papers presen- ted and 70 participants. A second Workshop of the
same na- ture has been decided to be held in Manchester (UMIST), -
gland, in April 1987. . The two volumes contain sufficient amount
of informa- tion which reflects very well the state-of-the-art of
the field, and shows the current tendency towards knowledge-ba- sed
(expert systems) and fault-tolerant approaches. Volume 1 contains
the contributions on fault diagnostics and reliability issues
(numeric treatment), and Vo*lume 2 the contributions on
knowledge~based and fault-tolerant techni- ques. We are grateful to
the Commission of the European Com- munities for having sponsored
the Workshop, and to all au- thors for their high quality
contributions and presenta- tions.
|
System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches - Volume 1 Fault Diagnostics and Reliability Proceedings of the First European Workshop on Fault Diagnostics, Reliability and Related Knowledge-Based Approaches, Island of Rhodes, Greece, August 31-September 3, 1986 (Hardcover, 1987 ed.)
S.G. Tzafestas, Madan Singh, Gunther Schmidt
|
R4,303
Discovery Miles 43 030
|
Ships in 10 - 15 working days
|
This book is devoted to the study of fuzzy reasoning as applied to
decision making and control processes. It contains a collection of
important contributions covering a wide well-selected range of
topics within the field. The book contains twenty-one papers,
written by thirty-four distinguished contributors and is divided
into five parts. Part 1 involves four chapters providing background
material together with useful techniques for the validation of
fuzzy knowledge bases and the software representation of fuzzy sets
and fuzzy logic. Part 2 presents an overview of neuro-fuzzy expert
systems along with an important case study, and a neural network
model which is suitable for fuzzy reasoning. Part 3 presents the
state of art of fuzzy controllers, including design and
implementation aspects. This part starts with a chapter on the
demystification of fuzzy control and includes critical evaluations
of fuzzy controllers, along with new types of fuzzy controllers
such as the sliding mode fuzzy controller. Part 4 involves a
chapter on fuzzy parameter and state estimation, which is of
fundamental importance in a variety of applications, a chapter on
fuzzy reasoning as used in rule-based systems, and a chapter on
computing the multivariable shape of an n-D pattern class. Finally,
Part 5 presents six important applications dealing with industrial
robotic systems, mechanical systems, manipulators with artificial
rubber muscles, Petri nets, biomedical engineering, and
nondestructive fruit collection. The book is suitable for the
researcher and practitioner, as well as for the teacher and student
in related Master and Doctoral courses.
This book is concerned with Intelligent Control methods and
applications. The field of intelligent control has been expanded
very much during the recent years and a solid body of theoretical
and practical results are now available. These results have been
obtained through the synergetic fusion of concepts and techniques
from a variety of fields such as automatic control, systems
science, computer science, neurophysiology and operational
research. Intelligent control systems have to perform
anthropomorphic tasks fully autonomously or interactively with the
human under known or unknown and uncertain environmental
conditions. Therefore the basic components of any intelligent
control system include cognition, perception, learning, sensing,
planning, numeric and symbolic processing, fault detection/repair,
reaction, and control action. These components must be linked in a
systematic, synergetic and efficient way. Predecessors of
intelligent control are adaptive control, self-organizing control,
and learning control which are well documented in the literature.
Typical application examples of intelligent controls are
intelligent robotic systems, intelligent manufacturing systems,
intelligent medical systems, and intelligent space teleoperators.
Intelligent controllers must employ both quantitative and
qualitative information and must be able to cope with severe
temporal and spatial variations, in addition to the fundamental
task of achieving the desired transient and steady-state
performance. Of course the level of intelligence required in each
particular application is a matter of discussion between the
designers and users. The current literature on intelligent control
is increasing, but the information is still available in a sparse
and disorganized way.
This book contains a selection of papers presented at the "European
Robotics and Intelligent Systems Conference" (EURISCON '91) held in
Corfu. Greece (June 23-28. 1991). It is devoted to the analysis.
design and applications of technological systems with built-in
intelligence achieved through appropriate blending of mathematical,
symbolic. sensing. computer processing. and feedback control
concepts. methods and software / hardware tools. System
intelligence includes human-like capabilities such as learning.
observation. perception. interpretation. reasoning. planning.
decision making. and action. Integrated intelligent decision and
control systems obey Saridis' prinCiple of Increasing Precision
with Decreasing Intelligence (IPDI). and have a hierarchical
structure with three basic levels. namely Organization.
Coordination. and Execution Levels. As we proceed from the
organization to the execution level. the precision about the jobs
to be completed increases and accordingly the intelligence reqUired
for these jobs decreases. As an example. it is mentioned here that
in an intelligent robotic system the organization tasks can be
realized using a neural net. the coordination tasks by a Petri net.
and the execution tasks by local sensors and actuators. The field
of intelligent systems is a new interdisciplinary field with
continuously increasing interest and expansion. It is actually the
outcome of the synergetic interaction and cooperation of classical
fields such as system theory. control theory. artificial
intelligence. operational research. information theory.
electronics. communications. and others.
The theory of nonlinear oscillations and stability of motion is a
fundamental part of the study of numerous real world phenomena.
These phenomena, particularly auto-oscillations of the first and
second kind, capture, para metric, subharmonic and ultraharmonic
resonance, asymptotic behavior and orbits' stability, constitute
the core of problems treated in "Nonlinear Mechanics", and their
study is connected with the names of H. Poincare, A. M. Lyapunov,
N. M. Krylov and N. N. Bogolyubov. Professor Demetrios Magiros, a
widely known scientist in the theories of oscillations and
nonlinear differential equations, has devoted his numerous works to
this significant part of modern physical science. His scientific
results can be classified in the following way: I) creation of
methods of analysis of subharmonic resonances under the nonlinear
effect, 2) determination and analysis of the main modes of
nonlinear oscillations on the basis of infinite determinants, 3)
analysis of problems of celestial mechanics, 4) classification of
stability of solutions of dynamic systems concepts, 5) mathematical
analogs of physical and social systems. He has developed new
methods and solutions for a great number of difficult problems of
nonlinear mechanics making a significant contri bution to the
theory and applications of the field. Urgency, depth of perception
of the considered phenomena, and practi cal directness are
characteristics of his work.
It is in the area of Systems Diagnosis. Supervision and Control
that Knowledge-Based Techniques have had their most significant
impact in recent years. In this volume. Spyros Tzafestas has ably
put together the current state of the art of the application of
Artificial Intelligence concepts to problems of Systems Diagnosis.
All the authors in this edited work are distinguished
internationally. recognized experts on various aspects of
Artificial Intelligence and its applications. and the coverage of
the field that they provide is both readable and authoritative. The
sixteen chapters break down in a natural way into three broad
categories i.e ** (a) introduction to the applications of Expert
Systems in Engineering. (b) Knowledge-based systems architectures.
models and techniques for fault diagnosis. supervision and real
time control and finally. (c) applications and case studies in
three specific 'areas. namely: Manufacturing. Chemical Processes
and Communications Networks. The final chapter provides a com
prehensive survey of the field with an extensive bibliography. The
mix of original scientific articles. tutorial and survey papers
makes this col lection a very timely and valuable addition to the
literature in this important field. MADAN G. SINGH Professor of
Information Engineering at U.M.I.S.T.
Great progresses have been made in the application of fuzzy set
theory and fuzzy logic. Most remarkable area of application is
'fuzzy control', where fuzzy logic was first applied to plant
control systems and its use is expanding to consumer products. Most
of fuzzy control systems uses fuzzy inference with max-min or
max-product composition, similar to the algorithm that first used
by Mamdani in 1970s. Some algorithms are developed to refine fuzzy
controls systems but the main part of algorithm stays the same.
Triggered by the success of fuzzy control systems, other ways of
applying fuzzy set theory are also investigated. They are usually
referred to as 'fuzzy expert sys tems', and their purpose are to
combine the idea of fuzzy theory with AI based approach toward
knowledge processing. These approaches can be more generally viewed
as 'fuzzy information processing', that is to bring fuzzy idea into
informa tion processing systems."
This book is concerned with Artificial Intelligence (AI) concepts
and techniques as applied to industrial decision making, control
and automation problems. The field of AI has been expanded
enormously during the last years due to that solid theoretical and
application results have accumulated. During the first stage of AI
development most workers in the field were content with
illustrations showing ideas at work on simple problems. Later, as
the field matured, emphasis was turned to demonstrations that
showed the capability of AI techniques to handle problems of
practical value. Now, we arrived at the stage where researchers and
practitioners are actually building AI systems that face real-world
and industrial problems. This volume provides a set of twenty four
well-selected contributions that deal with the application of AI to
such real-life and industrial problems. These contributions are
grouped and presented in five parts as follows: Part 1: General
Issues Part 2: Intelligent Systems Part 3: Neural Networks in
Modelling, Control and Scheduling Part 4: System Diagnostics Part
5: Industrial Robotic, Manufacturing and Organizational Systems
Part 1 involves four chapters providing background material and
dealing with general issues such as the conceptual integration of
qualitative and quantitative models, the treatment of timing
problems at system integration, and the investigation of correct
reasoning in interactive man-robot systems.
Robotics is a modern interdisciplinary field that has emerged from
the marriage of computerized numerical control and remote
manipulation. Today's robotic systems have intelligence features,
and are able to perform dexterous and intelligent human-like
actions through appropriate combination of learning, perception,
planning, decision making and control. This book presents advanced
concepts, techniques and applications reflecting the experience of
a wide group of specialists in the field. Topics include:
kinematics, dynamics, path planning and tracking, control, mobile
robotics, navigation, robot programming, and sophisticated
applications in the manufacturing, medical, and other areas.
This collection of twenty-three timely contributions covers a
well-selected repertory of topics within the autonomous systems
field. The book discusses a range of design, construction, control,
and operation problems along with a multiplicity of
well-established and novel solutions.
This book contains a selection of papers presented at the "European
Robotics and Intelligent Systems Conference" (EURISCON '91) held in
Corfu. Greece (June 23-28. 1991). It is devoted to the analysis.
design and applications of technological systems with built-in
intelligence achieved through appropriate blending of mathematical,
symbolic. sensing. computer processing. and feedback control
concepts. methods and software / hardware tools. System
intelligence includes human-like capabilities such as learning.
observation. perception. interpretation. reasoning. planning.
decision making. and action. Integrated intelligent decision and
control systems obey Saridis' prinCiple of Increasing Precision
with Decreasing Intelligence (IPDI). and have a hierarchical
structure with three basic levels. namely Organization.
Coordination. and Execution Levels. As we proceed from the
organization to the execution level. the precision about the jobs
to be completed increases and accordingly the intelligence reqUired
for these jobs decreases. As an example. it is mentioned here that
in an intelligent robotic system the organization tasks can be
realized using a neural net. the coordination tasks by a Petri net.
and the execution tasks by local sensors and actuators. The field
of intelligent systems is a new interdisciplinary field with
continuously increasing interest and expansion. It is actually the
outcome of the synergetic interaction and cooperation of classical
fields such as system theory. control theory. artificial
intelligence. operational research. information theory.
electronics. communications. and others.
This book is concerned with Intelligent Control methods and
applications. The field of intelligent control has been expanded
very much during the recent years and a solid body of theoretical
and practical results are now available. These results have been
obtained through the synergetic fusion of concepts and techniques
from a variety of fields such as automatic control, systems
science, computer science, neurophysiology and operational
research. Intelligent control systems have to perform
anthropomorphic tasks fully autonomously or interactively with the
human under known or unknown and uncertain environmental
conditions. Therefore the basic components of any intelligent
control system include cognition, perception, learning, sensing,
planning, numeric and symbolic processing, fault detection/repair,
reaction, and control action. These components must be linked in a
systematic, synergetic and efficient way. Predecessors of
intelligent control are adaptive control, self-organizing control,
and learning control which are well documented in the literature.
Typical application examples of intelligent controls are
intelligent robotic systems, intelligent manufacturing systems,
intelligent medical systems, and intelligent space teleoperators.
Intelligent controllers must employ both quantitative and
qualitative information and must be able to cope with severe
temporal and spatial variations, in addition to the fundamental
task of achieving the desired transient and steady-state
performance. Of course the level of intelligence required in each
particular application is a matter of discussion between the
designers and users. The current literature on intelligent control
is increasing, but the information is still available in a sparse
and disorganized way.
|
System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches - Volume 1 Fault Diagnostics and Reliability Proceedings of the First European Workshop on Fault Diagnostics, Reliability and Related Knowledge-Based Approaches, Island of Rhodes, Greece, August 31-September 3, 1986 (Paperback, Softcover reprint of the original 1st ed. 1987)
S.G. Tzafestas, Madan Singh, Gunther Schmidt
|
R4,273
Discovery Miles 42 730
|
Ships in 10 - 15 working days
|
The foundation of linear systems theory goes back to Newton and has
been followed over the years by many improvements such as linear
operator theory, Laplace Transformation etc. After the World War
II, feedback control theory has shown a rapid development, and
standard elegant analysis and synthesis techniques have been
discovered by control system workers, such as root-locus (Evans)
and frequency response methods (Nyquist, Bode). These permitted a
fast and efficient analysis of simple-loop control systems, but in
their original "paper-and-pencil" form were not appropriate for
multiple loop high-order systems. The advent of fast digital
computers, together with the development of multivariable
multi-loop system techniques, have eliminated these difficulties.
Multivariable control theory has followed two main avenues; the
optimal control approach, and the algebraic and frequency-domain
control approach. An important key concept in the whole
multivariable system theory is "ob servability and controllability"
which revealed the exact relationships between transfer functions
and the state variable representations. This has given new insight
into the phenomenon of "hidden oscillations" and to the transfer
function modelling of dynamic systems. The basic tool in optimal
control theory is the celebrated matrix Riccati differential
equation which provides the time-varying feedback gains in a
linear-quadratic control system cell. Much theory presently exists
for the characteristic properties and solution of this Riccati
equation."
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System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches - Volume 2 Knowledge-Based and Fault-Tolerant Techniques Proceedings of the First European Workshop on Fault Diagnostics, Reliability and Related Knowledge-Based Approaches, Island of Rhodes, Greece, August 31-September 3, 1986 (Paperback, Softcover reprint of the original 1st ed. 1987)
S.G. Tzafestas, Madan Singh, Gunther Schmidt
|
R5,475
Discovery Miles 54 750
|
Ships in 10 - 15 working days
|
This 2-volume work represents the proceedings of the First European
Workshop on Fault Diagnostics, Reliability and Re- lated
Knowledge-Based Approaches held in the Island of Rho- des, Greece
(August 3l-September 3, 1986). This Workshop was organized in the
framework of a joint research project spon- sored by the Commission
of the European Communi ties under the Stimulation Action
Programme. The principal aim of the Workshop was to bring together
people working on the numeric and symbolic (knowledge-based)
treatment of reliability and fault diagnosis problems, in order to
promote the interaction and exhange of ideas, expe- riences and
results in this area. The workshop was a real success, with SS
papers presen- ted and 70 participants. A second Workshop of the
same na- ture has been decided to be held in Manchester (UMIST), -
gland, in April 1987. . The two volumes contain sufficient amount
of informa- tion which reflects very well the state-of-the-art of
the field, and shows the current tendency towards knowledge-ba- sed
(expert systems) and fault-tolerant approaches. Volume 1 contains
the contributions on fault diagnostics and reliability issues
(numeric treatment), and Vo*lume 2 the contributions on
knowledge~based and fault-tolerant techni- ques. We are grateful to
the Commission of the European Com- munities for having sponsored
the Workshop, and to all au- thors for their high quality
contributions and presenta- tions.
In racent years the LSI technology has witnessed a revoluti onary
development, and allowed substantial reductions in the size and
cost of digital logic circuitry. Computer system building blocks
have progressed from the level of discrete components to the level
of complex ICs involving many logic circuits on a single "chip".
The invention and wide applica tions of microprocessors have
changed the philosophy of the signal processing, measurement and
control engineering fields. The microprocessor-based digital signal
processing systems and controllers have replaced the conventional
ones based on standard analog and digital computing equipment. The
first microprocessors and "on-chip" computers have appeared towards
the end of 71 beginning 72. Their evolution since then and the
number of applications, in which they have been utilized, have both
been extremely spectacular. New system concepts and
hardware/software tools are steadily under development to sup port
the microprocessor in its multiple and complex tasks. The goal of
this book is to provide a cohesive and well-balan ced set of
contributions dealing with important aspects and applications of
microprocessors to signal processing, measu rement and system
control. The majority of contributions in clude sufficient review
material and present rather complete treatments of the respective
topics.
The introduction of the microprocessor in computer and system
engineering has motivated the development of many new concepts and
has simplified the design of many modern industrial systems. During
the first decade of their life. microprocessors have shown a
tremendous evolution in all possible directions (technology. power.
functionality. I/O handling. etc). Of course putting the
microprocessors and their environmental devices into properly
operating systems is a complex and difficult task requiring high
skills for melding and integrating hardware. and systemic
components. software This book was motivated by the editors'
feeling that a cohesive reference is needed providing a good
coverage of modern industrial applications of microprocessor-based
real time control, together with latest advanced methodological
issues. Unavoidably a single volume cannot be exhaustive. but the
present book contains a sufficient number of important real-time
applications. The book is divided in two sections. Section I deals
with general hardware. software and systemic topics. and involves
six chapters. Chapter 1. by Gupta and Toong. presents an overview
of the development of microprocessors during their first twelve
years of existence. Chapter 2. by Dasgupta. deals with a number of
system software concepts for real time microprocessor-based systems
(task scheduling. memory management. input-output aspects.
programming language reqUirements."
This book contains thirty timely contributions in the emerging
field of Computational Intelligence (CI) with reference to system
control design and applications. The three basic constituents ofCI
are neural networks (NNs). fuzzy logic (FL) I fuzzy reasoning (FR).
and genetic algorithms (GAs). NNs mimic the distributed functioning
of the human brain and consist of many. rather simple. building
elements (called artificial neurons) which are controlled by
adaptive parameters and are able to incorporate via learning the
knowledge provided by the environment, and thus respond
intelligently to new stimuli. Fuzzy logic (FL) provides the means
to build systems that can reason linguistically under uncertainty
like the human experts (common sense reasoning). Both NNs and FL I
FR are among the most widely used tools for modeling unknown
systems with nonlinear behavior. FL suits better when there is some
kind of knowledge about the system. such as, for example, the
linguistic information of a human expert. On the other hand. NNs
possess unique learning and generalization capabilities that allow
the user to construct very accurate models of nonlinear systems
simply using input-output data. GAs offer an interesting set of
generic tools for systematic random search optimization following
the mechanisms of natural genetics. In hybrid Computational
Intelligence - based systems these three tools (NNs, FL, GAs) are
combined in several synergetic ways producing integrated tools with
enhanced learning, generalization. universal approximation.
reasoning and optimization abilities.
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