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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
This book provides basic theories and implementations using SCILAB open-source software for digital images. The book simplifies image processing theories and well as implementation of image processing algorithms, making it accessible to those with basic knowledge of image processing. This book includes many SCILAB programs at the end of each theory, which help in understanding concepts. The book includes more than sixty SCILAB programs of the image processing theory. In the appendix, readers will find a deeper glimpse into the research areas in the image processing.
The design of nonlinear controllers for mechanical systems has been an ex tremely active area of research in the last two decades. From a theoretical point of view, this attention can be attributed to their interesting dynamic behavior, which makes them suitable benchmarks for nonlinear control the oreticians. On the other hand, recent technological advances have produced many real-world engineering applications that require the automatic con trol of mechanical systems. the mechanism for de Often, Lyapunov-based techniques are utilized as veloping different nonlinear control structures for mechanical systems. The allure of the Lyapunov-based framework for mechanical system control de sign can most likely be assigned to the fact that Lyapunov function candi dates can often be crafted from physical insight into the mechanics of the system. That is, despite the nonlinearities, couplings, and/or the flexible effects associated with the system, Lyapunov-based techniques can often be used to analyze the stability of the closed-loop system by using an energy like function as the Lyapunov function candidate. In practice, the design procedure often tends to be an iterative process that results in the death of many trees. That is, the controller and energy-like function are often constructed in concert to foster an advantageous stability property and/or robustness property. Fortunately, over the last 15 years, many system the ory and control researchers have labored in this area to produce various design tools that can be applied in a variety of situations."
In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.
It is a great pleasure for me to introduce this book which has the main ambition to make thermodynamics more directly accessible to engineers and physicists by stressing the analogies with the other physical domains; this science has discouraged more than a few students. The book comes from the meeting of two persons: 1. Jean Thoma, inventor of hydrostatic machines and transmissions, pro fessor at the University of Waterloo (Canada), expert in simulation and pilgrim for the promotion of bond graphs around the world. 2. Belkacem Ould Bouamama, associated professor at the University of Science and Technology in Lille, France, specialist in industrial control and seduced by the richness and structure of the bond graph method. Thermodynamics is a difficult subject; its concepts like entropy, enthalpy, etc. are not intuitive and often very abstract. For this reason, it is current practice to neglect the thermal aspects, although they are necessarily there in all physical phenomena, and to use isothermal models. This is equivalent to think that the system is immersed in an infinite temperature reservoir and maintains its temperature constant even if it receives or dissipates electric and other type of energy. For heat transfer and variable temperature, if it should be included, the classical approach is to study the changes between equilibrium states, and not the process itself, which is more a thermostatic than a thermodynamic approach. This is justified when only the constraints of equilibrium state must be satisfied."
This book incorporates recent advances in the design of feedback laws to the purpose of globally stabilizing nonlinear systems via state or output feedback. It is a continuation of the first volume by Alberto Isidori on Nonlinear Control Systems. Specifically this second volume will cover: *Stability analysis of interconnected nonlinear systems. The notion of Input-to-State stability and its role in analysing stability of cascade-connected or feedback-connected systems. The notion of dissipativity and its consequences (passivity and "gain"). *Robust stabilization in the case of parametric uncertainties. The case of state feedback: global or semi-global stabilization. The case of output feedback: semi-global stabilization. *Robust stabilization in the case of unstructured perturbations. Feedback design via the small-gain approach. Robust semi-global stabilization via output feedback. *Methods for asymptotic tracking, disturbance rejection and model following. Global and semi-global analysis. *Normal forms for multi-input multi-output nonlinear systems form a global point of view. Their role in feedback design.
Providing a wide variety of technologies for ensuring the safety and dependability of cyber-physical systems (CPS), this book offers a comprehensive introduction to the architecture-centric modeling, analysis, and verification of CPS. In particular, it focuses on model driven engineering methods including architecture description languages, virtual prototyping, and formal analysis methods. CPS are based on a new design paradigm intended to enable emerging software-intensive systems. Embedded computers and networks monitor and control the physical processes, usually with the help of feedback loops where physical processes affect computations and vice versa. The principal challenges in system design lie in this constant interaction of software, hardware and physics. Developing reliable CPS has become a critical issue for the industry and society, because many applications such as transportation, power distribution, medical equipment and tele-medicine are dependent on CPS. Safety and security requirements must be ensured by means of powerful validation tools. Satisfying such requirements, including quality of service, implies having formally proven the required properties of the system before it is deployed. The book is concerned with internationally standardized modeling languages such as AADL, SysML, and MARTE. As the effectiveness of the technologies is demonstrated with industrial sample cases from the automotive and aerospace sectors, links between the methods presented and industrial problems are clearly understandable. Each chapter is self-contained, addressing specific scientific or engineering problems, and identifying further issues. In closing, it includes perspectives on future directions in CPS design from an architecture analysis viewpoint.
Over the past decades, although stochastic system control has been
studied intensively within the field of control engineering, all
the modelling and control strategies developed so far have
concentrated on the performance of one or two output properties of
the system. such as minimum variance control and mean value
control. The general assumption used in the formulation of
modelling and control strategies is that the distribution of the
random signals involved is Gaussian. In this book, a set of new
approaches for the control of the output probability density
function of stochastic dynamic systems (those subjected to any
bounded random inputs), has been developed. In this context, the
purpose of control system design becomes the selection of a control
signal that makes the shape of the system outputs p.d.f. as close
as possible to a given distribution. The book contains material on
the subjects of: - Control of single-input single-output and
multiple-input multiple-output stochastic systems; - Stable
adaptive control of stochastic distributions; - Model reference
adaptive control; - Control of nonlinear dynamic stochastic
systems; - Condition monitoring of bounded stochastic
distributions; - Control algorithm design; - Singular stochastic
systems.
"SAFEPROCESS '97" was the third in this major IFAC symposia series and covered a wide range of theoretical and application studies concerned with the reliability, availability and safety of controlled systems. The goal of the symposium was to bring together experts from different fields to give an overview of the state-of-the-art, present new research results and show future developments. In addition, there was special emphasis on industrial requirements for FDI (fault detection and isolation) and a new session on the human factors aspects of system monitoring and safety that reflects the growing interest in this area. These proceedings contain the 209 papers presented at the symposium and comprise: plenary overviews; state-of-the-art reviews and surveys; the very latest results; and tutorial papers.
* Provides an elegant introduction to the geometric concepts that are important to applications in robotics * Includes significant state-of-the art material that reflects important advances, connecting robotics back to mathematical fundamentals in group theory and geometry * An invaluable reference that serves a wide audience of grad students and researchers in mechanical engineering, computer science, and applied mathematics
Selected contributions to the Workshop WAFR 2002, held December 15-17, 2002, Nice, France. This fifth biannual Workshop on Algorithmic Foundations of Robotics focuses on algorithmic issues related to robotics and automation. The design and analysis of robot algorithms raises fundamental questions in computer science, computational geometry, mechanical modeling, operations research, control theory, and associated fields. The highly selective program highlights significant new results such as algorithmic models and complexity bounds. The validation of algorithms, design concepts, or techniques is the common thread running through this focused collection.
Piecewise Linear (PL) approximation of non-linear behaviour is a well-known technique in synthesis and analysis of electrical networks. However, the PL description should be efficient in data storage and the description should allow simple retrieval of the stored information. Furthermore, it would be useful if the model description could handle a large class of piecewise linear mappings. Piecewise Linear Modeling and Analysis explains in detail all possible model descriptions for efficiently storing piecewise linear functions, starting with the Chua descriptions. Detailed explanation on how the model parameter can be obtained for a given mapping is provided and demonstrated by examples. The models are ranked to compare them and to show which model can handle the largest class of PL mappings. All model descriptions are implicitly related to the Linear Complementarity Problem and most solution techniques for this problem, like Katzenelson and Lemke, are discussed according to examples that are explained in detail. To analyse PL electrical networks a simulator is mandatory. Piecewise Linear Modeling and Analysis provides a detailed outline of a possible PL simulator, including pseudo-programming code. Several simulation domains like transient, AC and distortion are discussed. The book explains the attractive features of PL simulators with respect to mixed-level and mixed-signal simulation while paying due regard also to hierarchical simulation. Piecewise Linear Modeling and Analysis shows in detail how many existing components in electrical networks can be modeled. These range from digital logic and analog basic elements such as transistors to complex systems like Phase-Locked Loops and detection systems. Simulation results are also provided. The book concludes with a discussion on how to find multiple solutions for PL functions or networks. Again, the most common techniques are outlined using clear examples. Piecewise Linear Modeling and Analysis is an indispensable guide for researchers and designers interested in network theory, network synthesis and network analysis.
Held from 3-5 September 1997 in Nantes, France, this was the fifth
of the IFAC series of triennial Symposia on Robot Control.
This book introduces non-identifier-based adaptive control (with and without internal model) and its application to the current, speed and position control of mechatronic systems such as electrical synchronous machines, wind turbine systems, industrial servo systems, and rigid-link, revolute-joint robots. In mechatronics, there is often only rough knowledge of the system. Due to parameter uncertainties, nonlinearities and unknown disturbances, model-based control strategies can reach their performance or stability limits without iterative controller design and performance evaluation, or system identification and parameter estimation. The non-identifier-based adaptive control presented is an alternative that neither identifies the system nor estimates its parameters but ensures stability. The adaptive controllers are easy to implement, compensate for disturbances and are inherently robust to parameter uncertainties and nonlinearities. For controller implementation only structural system knowledge (like relative degree, input-to-state stable zero dynamics and known sign of the high-frequency gain) is required. Moreover, the presented controllers guarantee reference tracking with prescribed asymptotic or transient accuracy, i.e. the tracking error eventually tends to or for all time evolves within an a priori specified region. The book presents the theory, modeling and application in a general but detailed and self-contained manner, making it easy to read and understand, particularly for newcomers to the topics covered
The international conference on Automation and Robotics-ICAR2011 is held during December 12-13, 2011 in Dubai, UAE. The proceedings of ICAR2011 have been published by Springer Lecture Notes in Electrical Engineering, which include 163 excellent papers selected from more than 400 submitted papers. The conference is intended to bring together the researchers and engineers/technologists working in different aspects of intelligent control systems and optimization, robotics and automation, signal processing, sensors, systems modeling and control, industrial engineering, production and management. This part of proceedings includes 81 papers contributed by many researchers in relevant topic areas covered at ICAR2011 from various countries such as France, Japan, USA, Korea and China etc. Many papers introduced their advanced research work recently; some of them gave a new solution to problems in the field, with powerful evidence and detail demonstration. Others stated the application of their designed and realized systems. The session topic of this proceeding is intelligent control and robotics and automation, which includes papers about Distributed Control Systems, Intelligent Fault Detection and Identification, Machine Learning in Control, Neural Networks based Control Systems, Fuzzy Control, Genetic Algorithms, Robot Design, Human-robots Interfaces, Network Robotics, and Autonomous Systems, Industrial Networks and Automation, Modeling, Simulation and Architectures, Vision, Recognition and Reconstruction, Virtual Reality, Image Processing, and so on. All of papers here involved the authors' numerous time and energy, will be proved valuable in their research field. Sincere thanks to the committee and all the authors, moreover anonymous reviewers from many fields and organizations. That is a power for all of us to go on research work for the world."
This book surveys the well-known results and also presents a series of original results on the mathematical modeling of social networks, focusing on models of informational influence, control and confrontation. Online social networks are intended for communication, opinion exchange and information acquisition for their members, but recently, online social networks have been intensively used as the objects and means of informational control and an arena of informational confrontation. They have become a powerful informational influence tool, particularly for the manipulation of individuals, social groups and society as a whole, as well as a battlefield of information warfare (cyberwars). This book aimed at under- and postgraduate university students as well as experts in information technology and modeling of social systems and processes.
This book presents an authoritative collection of contributions by researchers from 16 different countries (Austria, Chile, Georgia, Germany, Mexico, Norway, P.R. of China, Poland, North Macedonia, Romania, Russia, Spain, Turkey, Ukraine, the United Kingdom and United States) that report on recent developments and new directions in advanced control systems, together with new theoretical findings, industrial applications and case studies on complex engineering systems. This book is dedicated to Professor Vsevolod Mykhailovych Kuntsevich, an Academician of the National Academy of Sciences of Ukraine, and President of the National Committee of the Ukrainian Association on Automatic Control, in recognition of his pioneering works, his great scientific and scholarly achievements, and his years of service to many scientific and professional communities, notably those involved in automation, cybernetics, control, management and, more specifically, the fundamentals and applications of tools and techniques for dealing with uncertain information, robustness, non-linearity, extremal systems, discrete control systems, adaptive control systems and others. Covering essential theories, methods and new challenges in control systems design, the book is not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike. Its 15 chapters are grouped into four sections: (a) fundamental theoretical issues in complex engineering systems, (b) artificial intelligence and soft computing for control and decision-making systems, (c) advanced control techniques for industrial and collaborative automation, and (d) modern applications for management and information processing in complex systems. All chapters are intended to provide an easy-to-follow introduction to the topics addressed, including the most relevant references. At the same time, they reflect various aspects of the latest research work being conducted around the world and, therefore, provide information on the state of the art.
This book presents an operator theoretic approach to robust control analysis for linear time-varying systems. It emphasizes the conceptual similarity with the H control theory for time-invariant systems and at the same time clarifies the major difficulties confronted in the time varying case. The necessary operator theory is developed from first principles and the book is as self-contained as possible. After presenting the necessary results from the theories of Toeplitz operators and nest algebras, linear systems are defined as input- output operators and the relationship between stabilization and the existance of co-prime factorizations is described. Uniform optimal control problems are formulated as model-matching problems and are reduced to four block problems. Robustness is considered both from the point of view of fractional representations and the "time varying gap" metric, and the relationship between these types of uncertainties is clarified. The book closes with the solution of the orthogonal embedding problem for time varying contractive systems. This book will be useful to both mathematicians interested in the potential applications of operator theory in control and control engineers who wish to deal with some of the more mathematically sophisticated extension of their work.
This monograph presents a new analytical approach to the design of proportional-integral-derivative (PID) controllers for linear time-invariant plants. The authors develop a computer-aided procedure, to synthesize PID controllers that satisfy multiple design specifications. A geometric approach, which can be used to determine such designs methodically using 2- and 3-D computer graphics is the result. The text expands on the computation of the complete stabilizing set previously developed by the authors and presented here. This set is then systematically exploited to achieve multiple design specifications simultaneously. These specifications include classical gain and phase margins, time-delay tolerance, settling time and H-infinity norm bounds. The results are developed for continuous- and discrete-time systems. An extension to multivariable systems is also included. Analytical Design of PID Controllers provides a novel method of designing PID controllers, which makes it ideal for both researchers and professionals working in traditional industries as well as those connected with unmanned aerial vehicles, driverless cars and autonomous robots.
Complexity and dynamic order of controlled engineering systems is constantly increasing. Complex large scale systems (where "large" reflects the system's order and not necessarily its physical size) appear in many engineering fields, such as micro-electromechanics, manufacturing, aerospace, civil engineering and power engineering. Modeling of these systems often result in very high-order models imposing great challenges to the analysis, design and control problems. "Efficient Modeling and Control of Large-Scale Systems" compiles state-of-the-art contributions on recent analytical and computational methods for addressing model reduction, performance analysis and feedback control design for such systems. Also addressed at length are new theoretical developments, novel computational approaches and illustrative applications to various fields, along with: - An interdisciplinary focus emphasizing methods and approaches that can be commonly applied in various engineering fields -Examinations of applications in various fields including micro-electromechanical systems (MEMS), manufacturing processes, power networks, traffic control "Efficient Modeling and Control of Large-Scale Systems" is an ideal volume for engineers and researchers working in the fields of control and dynamic systems.
The author presents current work in bond graph methodology by
providing a compilation of contributions from experts across the
world that covers theoretical topics, applications in various areas
as well as software for bond graph modeling.
This edited book aims at presenting current research activities in the field of robust variable-structure systems. The scope equally comprises highlighting novel methodological aspects as well as presenting the use of variable-structure techniques in industrial applications including their efficient implementation on hardware for real-time control. The target audience primarily comprises research experts in the field of control theory and nonlinear dynamics but the book may also be beneficial for graduate students.
The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications. "
Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.
"Hybrid Predictive Control for Dynamic Transport Problems" develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: . hybrid predictive control (HPC) design based on evolutionary multiobjective optimization (EMO); . HPC based on EMO for dial-a-ride systems; and . HPC based on EMO for operational decisions in public transport systems. "Hybrid Predictive Control for Dynamic Transport Problems" is a comprehensive analysis of HPC and its application to dynamic transport systems. Introductory material on evolutionary algorithms is presented in summary in an appendix. The text will be of interest to control and transport engineers working on the operational optimization of transport systems and to academic researchers working with hybrid systems. The potential applications of the generic methods presented here to other process fields will make the book of interest to a wider group of researchers, scientists and graduate students working in other control-related disciplines."
The ability of fuzzy systems to provide shades of gray between "on or off" and "yes or no" is ideally suited to many of todaya (TM)s complex industrial control systems. The static fuzzy systems usually discussed in this context fail to take account of inputs outside a pre-set range and their off-line nature makes tuning complicated. Advanced Fuzzy Logic Technologies in Industrial Applications addresses the problem by introducing a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The tuning process is a major focus in this volume because it is the most difficult stage in fuzzy control application. Using new methods such as A-law technique, histogram equalization and the Bezier-based method, all detailed here, the tuning process can be significantly simplified and control performance improved. The other great strength of this book lies in the range and contemporaneity of its applications and examples which include: laser tracking and control; robot calibration; image processing and pattern recognition; medical engineering; audio systems; autonomous underwater vehicles and data mining. Advanced Fuzzy Logic Technologies in Industrial Applications is written to be easily understood by readers not having specialized knowledge of fuzzy logic and intelligent control. Design and application engineers and project managers working in control, as well as researchers and graduate students in the discipline will find much to interest them in this work. |
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