The book largely represents the extended version of select papers from the Inter- tional Conference on Intelligent Unmanned System ICIUS 2007 which was jointly organized by the Center for Unmanned System Studies at Institut Teknologi Bandung, Artificial Muscle Research Center at Konkuk University and Institute of Bio-inspired Structure and Surface Engineering, Nanjing University of Aeronautics and Astrona- ics. The joint-event was the 3rd conference extending from International Conference on Emerging System Technology (ICEST) in 2005 and International Conference on Technology Fusion (ICTF) in 2006 both conducted in Seoul. ICIUS 2007 was focused on both theory and application primarily covering the topics on robotics, autonomous vehicles and intelligent unmanned technologies. The conference was arranged into three parallel symposia with the following scope of topics: Unmanned Systems: Micro air vehicle, Underwater vehicle, Micro-satellite, - manned aerial vehicle, Multi-agent systems, Autonomous ground vehicle, Blimp, Swarm intelligence, learning and control Robotics and Biomimetics: Artificial muscle actuators, Smart sensors, Design and applications of MEMS/NEMS system, Intelligent robot system, Evolutionary al- rithm, Control of biological systems, AI and expert systems, Biological learning control systems, Neural networks, Genetic algorithm Control and Intelligent System: Distributed intelligence, Distributed/decentralized intelligent control, Distributed or decentralized control methods, Distributed and - bedded systems, Embedded intelligent control, Complex systems, Discrete event s- tems, Hybrid systems, Networked control systems, Delay systems, Fuzzy systems, Identification and estimation, Nonlinear systems, Precision motion control, Control applications, Control engineering education.

This thesis investigates the use of blade-pitch control and real-time wind measurements to reduce the structural loads on the rotors and blades of wind turbines. The first part of the thesis studies the main similarities between the various classes of current blade-pitch control strategies, which have to date remained overlooked by mainstream literature. It also investigates the feasibility of an estimator design that extracts the turbine tower motion signal from the blade load measurements. In turn, the second part of the thesis proposes a novel model predictive control layer in the control architecture that enables an existing controller to incorporate the upcoming wind information and constraint-handling features. This thesis provides essential clarifications of and systematic design guidelines for these topics, which can benefit the design of wind turbines and, it is hoped, inspire the development of more innovative mechanical load-reduction solutions in the field of wind energy.

To describe the true behavior of most real-world systems with sufficient accuracy, engineers have to overcome difficulties arising from their lack of knowledge about certain parts of a process or from the impossibility of characterizing it with absolute certainty. Depending on the application at hand, uncertainties in modeling and measurements can be represented in different ways. For example, bounded uncertainties can be described by intervals, affine forms or general polynomial enclosures such as Taylor models, whereas stochastic uncertainties can be characterized in the form of a distribution described, for example, by the mean value, the standard deviation and higher-order moments.

The goal of this Special Volume on "Modeling, Design, and Simulation of Systems with Uncertainties" is to cover modern methods for dealing with the challenges presented by imprecise or unavailable information. All contributions tackle the topic from the point of view of control, state and parameter estimation, optimization and simulation.

Thematically, this volume can be divided into two parts. In the first we present works highlighting the theoretic background and current research on algorithmic approaches in the field of uncertainty handling, together with their reliable software implementation. The second part is concerned with real-life application scenarios from various areas including but not limited to mechatronics, robotics, and biomedical engineering.

A complete reference to adaptive control of systems with nonsmooth industrial nonlinearities such as:- backlash- dead-zones- component failure- friction- hysteresis- saturation- time delays. These nonlinearities in industrial actuators cause severe problems in the motion control of industrial processes, particularly in view of modern requirements of speed and precision of movement such as occur in semiconductor manufacturing, precision machining, and elsewhere. Actuator nonlinearities are ubiquitous in engineering practice and limit control system performance. While standard feedback control alone cannot handle these nonsmooth nonlinearities effectively, this book, with unified and systematic adaptive design methods developed in 16 chapters, shows how such nonlinear characteristics can be effectively compensated for by using adaptive and intelligent control techniques. This allows desired system performance to be achieved in the presence of uncertain nonlinearities. With extensive surveys of literature and comprehensive summaries of various design methods, the authors of the book chapters, who are experts in their areas of interest, present new solutions to some important issues in adaptive control of systems with various sorts of nonsmooth nonlinearities.In addition to providing solutions, the book is also aimed at motivating more research activities in the important field of adaptive control of nonsmooth nonlinear industrial systems by formulating several challenging open problems in related areas.

This edited volume contains sixteen research articles and presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. It assembles experts from the fields of operations research, control theory and optimization, stochastic analysis, and financial engineering to review and substantially update the recent progress in these fields. Another distinct characteristic of the book is that all papers are motivated by applications in which optimization, control, and stochastics are inseparable. The book will be a timely addition to the literature and will be of interest to people working in the aforementioned fields.

Most importantly, this volume is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday. In view of his fundamental contributions, his distinguished career, his substantial achievements, his influence on the areas of control theory and applications, operations research, and management science, and his dedication to the scientific community, a number of leading experts in the fields of optimization, control, and operation management, have contributed to this volume in honor of him.

The book reports on the latest advances in and applications of chaos theory and intelligent control. Written by eminent scientists and active researchers and using a clear, matter-of-fact style, it covers advanced theories, methods, and applications in a variety of research areas, and explains key concepts in modeling, analysis, and control of chaotic and hyperchaotic systems. Topics include fractional chaotic systems, chaos control, chaos synchronization, memristors, jerk circuits, chaotic systems with hidden attractors, mechanical and biological chaos, and circuit realization of chaotic systems. The book further covers fuzzy logic controllers, evolutionary algorithms, swarm intelligence, and petri nets among other topics. Not only does it provide the readers with chaos fundamentals and intelligent control-based algorithms; it also discusses key applications of chaos as well as multidisciplinary solutions developed via intelligent control. The book is a timely and comprehensive reference guide for graduate students, researchers, and practitioners in the areas of chaos theory and intelligent control.

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."

"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."

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.
A new representation of dynamic stochastic systems is produced by using B-spline functions to descripe the output p.d.f. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Microsystems are an important success factor in the automobile industry. In order to fulfil the customers' requests for safety convenience and vehicle economy, and to satisfy environmental requirements, microsystems are becoming indispensable. Thus a large number of microsystem applications came into the discussion. With the international conference AMAA 2000, VDI/VDE-IT provides a platform for the discussion of all MST relevant components for automotive applications. The conference proceedings gather the papers by authors from automobile suppliers and manufacturers.

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.

In the mathematical treatment of many problems which arise in physics, economics, engineering, management, etc., the researcher frequently faces two major difficulties: infinite dimensionality and randomness of the evolution process. Infinite dimensionality occurs when the evolution in time of a process is accompanied by a space-like dependence; for example, spatial distribution of the temperature for a heat-conductor, spatial dependence of the time-varying displacement of a membrane subject to external forces, etc. Randomness is intrinsic to the mathematical formulation of many phenomena, such as fluctuation in the stock market, or noise in communication networks. Control theory of distributed parameter systems and stochastic systems focuses on physical phenomena which are governed by partial differential equations, delay-differential equations, integral differential equations, etc., and stochastic differential equations of various types. This has been a fertile field of research with over 40 years of history, which continues to be very active under the thrust of new emerging applications. Among the subjects covered are: Control of distributed parameter systems; Stochastic control; Applications in finance/insurance/manufacturing; Adapted control; Numerical approximation . It is essential reading for applied mathematicians, control theorists, economic/financial analysts and engineers.

The Engineering of Complex Real-Time Computer Control Systems brings together in one place important contributions and up-to-date research results in this important area. The Engineering of Complex Real-Time Computer Control Systems serves as an excellent reference, providing insight into some of the most important research issues in the field.

This book provides a comprehensive discussion of nonlinear multi-modal structural vibration problems, and shows how vibration suppression can be applied to such systems by considering a sample set of relevant control techniques. It covers the basic principles of nonlinear vibrations that occur in flexible and/or adaptive structures, with an emphasis on engineering analysis and relevant control techniques. Understanding nonlinear vibrations is becoming increasingly important in a range of engineering applications, particularly in the design of flexible structures such as aircraft, satellites, bridges, and sports stadia. There is an increasing trend towards lighter structures, with increased slenderness, often made of new composite materials and requiring some form of deployment and/or active vibration control. There are also applications in the areas of robotics, mechatronics, micro electrical mechanical systems, non-destructive testing and related disciplines such as structural health monitoring. Two broader themes cut across these application areas: (i) vibration suppression - or active damping - and, (ii) adaptive structures and machines. In this expanded 2nd edition, revisions include: An additional section on passive vibration control, including nonlinear vibration mounts. A more in-depth description of semi-active control, including switching and continuous schemes for dampers and other semi-active systems. A complet e reworking of normal form analysis, which now includes new material on internal resonance, bifurcation of backbone curves and stability analysis of forced responses.Further analysis of the nonlinear dynamics of cables including internal resonance leading to whirling. Additional material on the vibration of systems with impact friction. The book is accessible to practitioners in the areas of application, as well as students and researchers working on related topics. In particular, the aim is to introduce the key concepts of nonlinear vibration to readers who have an understanding of linear vibration and/or linear control, but no specialist knowledge in nonlinear dynamics or nonlinear control.

This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.

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.

Nonlinear and Adaptive Control with Applications provides a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. The authors employ a new tool based on the ideas of system immersion and manifold invariance. Departing, in part, from the Lyapunov-function approach of classical control, new algorithms are delivered for the construction of robust asymptotically-stabilising and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes. These algorithms cater for nonlinear systems with both parametric and dynamic uncertainties. This innovative strategy is illustrated with several examples and case studies from real applications. Power converters, electrical machines, mechanical systems, autonomous aircraft and computer vision are among the practical systems dealt with. Researchers working on adaptive and nonlinear control theory or on control applications will find this monograph of conspicuous interest while graduate students in control systems and control engineers working with electrical, mechanical or electromechanical systems can also gain much insight and assistance from the methods and algorithms detailed.

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.

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.

This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.

This book, written by experts in the field, is based on the latest research on the analysis and synthesis of switched time-delay systems. It covers the stability, filtering, fault detection and control problems, which are studied using the average dwell time approach. It presents both the continuous-time and discrete-time systems and provides useful insights and methods, as well as practical algorithms that can be considered in other complex systems, such as neuron networks and genetic regulatory networks, making it a valuable resource for researchers, scientists and engineers in the field of system sciences and control communities.

Technology has been the spark that ignited NATO's interest and commitment to scientific advancement during its history. Since its creation, the Science for Peace and Security (SPS) Programme has been instrumental to NATO's commitment to innovation, science and technological advancement. During the years, SPS has demonstrated a flexible and versatile approach to practical scientific cooperation, and has promoted knowledge-sharing, building capacity, and projected stability outside NATO territory. The priorities addressed by the SPS Programme are aligned with NATO's strategic objectives, and aim to tackle emerging security challenges that require dynamic adaptation for the prevention and mitigation of risks. By addressing priorities such as advanced technologies, hybrid threats, and counter-terrorism, the Programme deals with new, contemporary challenges. On 17-18 September 2019, the SPS Programme gathered at the KU Leuven University a wide number of researchers from a selection of on-going and recently closed SPS projects in the field of security-related advanced technologies for a "Cluster Workshop on Advanced Technologies". The workshop covered, in particular, the following scientific domains: communication systems, advanced materials, sensors and detectors, and unmanned and autonomous systems. This book provides an overview on how these projects have contributed to the development of new technologies and innovative solutions and recommendations for future actions in the NATO SPS programme.

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.

Geared primarily to an audience consisting of mathematically advanced undergraduate or beginning graduate students, this text may additionally be used by engineering students interested in a rigorous, proof-oriented systems course that goes beyond the classical frequency-domain material and more applied courses. The minimal mathematical background required is a working knowledge of linear algebra and differential equations. The book covers what constitutes the common core of control theory and is unique in its emphasis on foundational aspects. While covering a wide range of topics written in a standard theorem/proof style, it also develops the necessary techniques from scratch. In this second edition, new chapters and sections have been added, dealing with time optimal control of linear systems, variational and numerical approaches to nonlinear control, nonlinear controllability via Lie-algebraic methods, and controllability of recurrent nets and of linear systems with bounded controls.