This 2001 book presents a general theory as well as a constructive methodology to solve 'observation problems', that is, reconstructing the full information about a dynamical process on the basis of partial observed data. A general methodology to control processes on the basis of the observations is also developed. Illustrative but also practical applications in the chemical and petroleum industries are shown. This book is intended for use by scientists in the areas of automatic control, mathematics, chemical engineering and physics.

This fascinating book examines some of the characteristics of technological/engineering models that are likely to be unfamiliar to those who are interested primarily in the history and philosophy of science and mathematics, and which differentiate technological models from scientific and mathematical ones. Themes that are highlighted include:
the role of language: the models developed for engineering design have resulted in new ways of talking about technological systems
communities of practice: related to the previous point, particular engineering communities have particular ways of sharing and developing knowledge
graphical (re)presentation: engineers have developed many ways of reducing quite complex mathematical models to more simple representations
reification: highly abstract mathematical models are turned into 'objects' that can be manipulated almost like components of a physical system
machines: not only the currently ubiquitous digital computer, but also older analogue devices - slide rules, physical models, wind tunnels and other small-scale simulators, as well as mechanical, electrical and electronic analogue computers
mathematics and modelling as a bridging tool between disciplines
This book studies primarily modelling in technological practice. It is worth noting that models of the type considered in the book are not always highly valued in formal engineering education at university level, which often takes an "applied science" approach close to that of the natural sciences (something that can result in disaffection on the part of students). Yet in an informal context, such as laboratories, industrial placements, and so on, a very different situation obtains. A number of chapters considers such epistemological aspects, as well as the status of different types of models within the engineering education community.
The book will be of interest to practising engineers and technologists; sociologists of science and technology; and historians and philosophers of science and mathematics. It will also be written in a way that will be accessible to non-specialists."

As robots improve in efficiency and intelligence, there is a growing need to develop more efficient, accurate and powerful sensors in accordance with the tasks to be robotized. This has led to a great increase in the study and development of different kinds of sensor devices and perception systems over the last ten years. Applications that differ from the industrial ones are often more demanding in sensorics since the environment is not usually so well structured. Spatial and agricultural applications are examples of situations where the environment is unknown or variable. Therefore, the work to be done by a robot cannot be strictly programmed and there must be an interactive communication with the environment. It cannot be denied that evolution and development in robotics are closely related to the advances made in sensorics. The first vision and force sensors utilizing discrete components resulted in a very low resolution and poor accuracy. However, progress in VLSI, imaging devices and other technologies have led to the development of more efficient sensor and perception systems which are able to supply the necessary data to robots.

This volume offers comprehensive coverage of intelligent systems, including fundamental aspects, software-, sensors-, and hardware-related issues. Moreover, the contributors to this volume provide, beyond a systematic overview of intelligent interfaces and systems, deep, practical knowledge in building and using intelligent systems in various applications. Special emphasis is placed on specific aspects and requirements in applications.

The subject of the book is the "know-how" of applied mathematical modelling: how to construct specific models and adjust them to a new engineering environment or more precise realistic assumptions; how to analyze models for the purpose of investigating real life phenomena; and how the models can extend our knowledge about a specific engineering process. Two major sources of the book are the stock of classic models and the authors' wide experience in the field. The book provides a theoretical background to guide the development of practical models and their investigation. It considers general modelling techniques, explains basic underlying physical laws and shows how to transform them into a set of mathematical equations. The emphasis is placed on common features of the modelling process in various applications as well as on complications and generalizations of models. The book covers a variety of applications: mechanical, acoustical, physical and electrical, water transportation and contamination processes; bioengineering and population control; production systems and technical equipment renovation. Mathematical tools include partial and ordinary differential equations, difference and integral equations, the calculus of variations, optimal control, bifurcation methods, and related subjects.

In 1945, Dr. Ernst Weber founded, and was the first Director of, the Microwave Research Institute (MRI) at Polytechnic University (at that time named the Polytechnic Institute of Brooklyn). MRI gained worldwide recognition in the 50s and 60s for its research in electromagnetic theory, antennas and radiation, network theory and microwave networks, microwave components, and devices. It was also known through its series of 24 topical symposia and the widely distributed hardbound MRI Symposium Proceedings. Rededicated as the Weber Research Institute (WRI) in 1986, the institute currently conducts research in such areas as electromagnetic propagation and antennas, ultrabroadband electromagnetics, pulse power, acoustics, gaseous electronics, plasma physics, solid-state materials, quantum electronics, electromagnetic launchers, and networks. Following MRI tradition, WRI has launched its own series of in-depth topical conferences with published proceedings. Previous conferences in this series were: Directions in Electromagnetic Wave Modeling; October 1990 Ultra-Wideband Short-Pulse Electromagnetics; October, 1992 Ultra-Wideband Short-Pulse Electromagnetics, II; October, 1994 The proceedings of these conferences were also published by Plenum Press. This volume constitutes the proceedings of the fourth WRI International Conference dealing with Guided-Wave Optoelectronics: Device Characterization, Analysis and Design. The conference was held October 26-28, 1994, at the Polytechnic University in Brooklyn, New York, in cooperation with the IEEE Lasers and Electro Optics Society, and with the Optical Society of America. Theodor Tamir Giora Griffel Henry L. Bertoni v CONTENTS INTRODUCTORY Scanning the symposium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . T. Tamir and G. Griffel Photonics in telecommunications. . . . . . . . . . . . . . . . . . . . . . . 3 . . . . . . . . . H."

This book is a result of the Seventh International Conference on Information Sys tems Development-Methods and Tools, Theory and Practice held in Bled, Slovenia, Sep tember 21-23, 1998. The purpose of the conference was to address issues facing academia and industry when specifying, developing, managing, and improving information comput erized systems. During the past few years, many new concepts and approaches emerged in the Information Systems Development (ISD) field. The various theories, methods, and tools available to system developers also bring problems such as choosing the most effec tive approach for a specific task. This conference provides a meeting place for IS re searchers and practitioners from Eastern and Western Europe as well as from other parts of the world. An objective of the conference is not only to share scientific knowledge and in terests but to establish strong professional ties among the participants. The Seventh International Conference on Information Systems Develop ment-ISD'98 continues the concepts of the first Polish-Scandinavian Seminar on Current Trends in Information Systems Development Methodologies held in Gdansk, Poland in 1988. Through the years, the Seminar developed into the International Conference on In formation Systems Development. ISD'99 will be held in Boise, Idaho. The selection of papers was carried out by the International Program Committee. All papers were reviewed in advance by three people. Papers were judged according to their originality, relevance, and presentation quality. All papers were judged only on their own merits, independent of other submissions.

This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.

Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs."

The events leading up to the publication of this book started effectively in 1976 with the exchange of information between those modelling teams in Europe which were involved in the R&D-programme on Solar Energy of the Commission. When it became clear that the availability of experimental datafor model validation wm next to nothing, the Commission took the initiative to support in the frame of the Solar Energy R&D-programme the construction of Solar Pilot Test Facilities on eight sites in Europe. Each experimental facility consisted of two real solar heating systems with collectors, storage, controls, and msociated piping, but with the dwelling thermal distribution system replaced by a physical load simulator. One of the two systems on each site wm a reference system and wm identical for the eight participating teams. The simulator wm capable of producing a typical themalload for a house, interactive with the actual weather, and took into account the effects of the occupants. With datafrom these facilities not only were national simulation programs validated, but also the meanwhile commonly accepted modular structured European program EMGPl wm validated. EMGPl, which only could be run on a mainframe computer or under special conditions on a mini-computer, formed in tum the bmis for the development of EURSOL andEMGP3.EMGP3 is an improved userjriendly programpackagejorpersonal computers derived jrom EMGPl and includes a unique and user jriendly preprocessor.

This illustrated book provides a modern investigation into the bifurcation phenomena of physical and engineering problems. Systematic methods are used to examine experimental and computational data from numerous examples (soil, sand, kaolin, concrete, domes).

This book is a result of the ISD'99, Eight International Conference on Infonnation Systems Development-Methods and Tools, Theory, and Practice held August 11-13, 1999 in Boise, Idaho, USA. The purpose of this conference was to address the issues facing academia and industry when specifying, developing, managing, and improving infonnation systems. ISD'99 consisted not only of the technical program represented in these Proceedings, but also of plenary sessions on product support and content management systems for the Internet environment, workshop on a new paradigm for successful acquisition of infonnation systems, and a panel discussion on current pedagogical issues in systems analysis and design. The selection of papers for ISD'99 was carried out by the International Program Committee. Papers presented during the conference and printed in this volume have been selected from submissions after fonnal double-blind reviewing process and have been revised by their authors based on the recommendations of reviewers. Papers were judged according to their originality, relevance, and presentation quality. All papers were judged purely on their own merits, independently of other submissions. We would like to thank the authors of papers accepted for ISD'99 who all made gallant efforts to provide us with electronic copies of their manuscripts confonning to common guidelines. We thank them for thoughtfully responding to reviewers comments and carefully preparing their final contributions. We thank Daryl Jones, provost of Boise State University and William Lathen, dean, College of Business and Economics, for their support and encouragement.

This volume provides the proceedings of the First European Workshop on Parallel Processing Techniques for Simulation which was held at the end of October 1985. The Workshop was organized within the framework of a joint project sponsored by the Commission of the European Communities under the research part of the multiannua1 programme in the field of Data Processing aming at promoting collaborative research work in the Community. The project involved collaborative work between the Complex Systems Group of the Control Systems Centre at UMIST, the Systems Reliability Service of the United Kingdom Atomic Energy Authority and the University of Bergamo, Italy. The aim of this project was to develop decomposition coordination techniques which would be of help in the simulation of complex dynamical systems on parallel processing facilities. One of the major aims of the Workshop was to report on the results produced within the project and to try to relate these to the leading work going on in this field in other centres of excellence. With this in mind, the Proceedings Volume is split up into a number of parts corresponding to the main sessions within the Workshop programme.

Mathematical models have been very successful in the study of the physical world. Galilei and Newton introduced point particles moving without friction under the action of simple forces as the basis for the description of concrete motions like the ones of the planets. This approach was sustained by appro priate mathematical methods, namely infinitesimal calculus, which was being developed at that time. In this way classical analytical mechanics was able to establish some general results, gaining insight through explicit solution of some simple cases and developing various methods of approximation for handling more complicated ones. Special relativity theory can be seen as an extension of this kind of modelling. In the study of electromagnetic phenomena and in general relativity another mathematical model is used, in which the concept of classical field plays the fundamental role. The equations of motion here are partial differential equations, and the methods of study used involve further developments of classical analysis. These models are deterministic in nature. However it was realized already in the second half of last century, through the work of Maxwell, Boltzmann, Gibbs and others, that in the discussion of systems involving a great number of particles, the deterministic description is not by itself of great help, in particu lar a suitable "weighting" of all possible initial conditions should be considered."

This book is primarily a research monograph that presents in a unified man ner some recent research on a class of hybrid dynamical systems (HDS). The book is intended both for researchers and advanced postgraduate stu dents working in the areas of control engineering, theoretical computer science, or applied mathematics and with an interest in the emerging field of hybrid dynamical systems. The book assumes competence in the basic mathematical techniques of modern control theory. The material presented in this book derives from a period of fruitful research collaboration between the authors that began in 1994 and is still ongoing. Some of the material contained herein has appeared as isolated results in journal papers and conference proceedings. This work presents this material in an integrated and coherent manner and also presents many new results. Much of the material arose from joint work with students and colleagues, and the authors wish to acknowledge the major contributions made by Ian Petersen, Efstratios Skafidas, Valery Ugrinovskii, David Cook, Iven Mareels, and Bill Moran. There is currently no precise definition of a hybrid dynamical system; however, in broad terms it is a dynamical system that involves a mixture of discrete-valued and continuous-valued variables. Since the early 1990s, a bewildering array of results have appeared under the umbrella of HDS, ranging from the analysis of elementary on-off control systems to sophis ticated mathematical logic-based descriptions of large real-time software systems.

The analysis and design of engineering and industrial systems has come to rely heavily on the use of optimization techniques. The theory developed over the last 40 years, coupled with an increasing number of powerful computational procedures, has made it possible to routinely solve problems arising in such diverse fields as aircraft design, material flow, curve fitting, capital expansion, and oil refining just to name a few. Mathematical programming plays a central role in each of these areas and can be considered the primary tool for systems optimization. Limits have been placed on the types of problems that can be solved, though, by the difficulty of handling functions that are not everywhere differentiable. To deal with real applications, it is often necessary to be able to optimize functions that while continuous are not differentiable in the classical sense. As the title of the book indicates, our chief concern is with (i) nondifferentiable mathematical programs, and (ii) two-level optimization problems. In the first half of the book, we study basic theory for general smooth and nonsmooth functions of many variables. After providing some background, we extend traditional (differentiable) nonlinear programming to the nondifferentiable case. The term used for the resultant problem is nondifferentiable mathematical programming. The major focus is on the derivation of optimality conditions for general nondifferentiable nonlinear programs. We introduce the concept of the generalized gradient and derive Kuhn-Tucker-type optimality conditions for the corresponding formulations.

This book introduces the reader to a novel method of mathematical description, analysis and design of digital control systems, which makes it possible to take into account, in the most complete form, specific features of interaction between continuous-time and discrete time processes.

Agent-based modeling and social simulation have emerged as an interdisciplinary area of social science that includes computational economics, organizational science, social dynamics, and complex systems. This area contributes to enriching our understanding of the fundamental processes of social phenomena caused by complex interactions among agents. Bringing together diverse approaches to social simulation and research agendas, this book presents a unique collection of contributions from the Second World Congress on Social Simulation, held in 2008 at George Mason University in Washington DC, USA. This book in particular includes articles on norms, diffusion, social networks, economy, markets and organizations, computational modeling, and programming environments, providing new hypotheses and theories, new simulation experiments compared with various data sets, and new methods for model design and development. These works emerged from a global and interdisciplinary scientific community of the three regional scientific associations for social simulation: the North American Association for Computational Social and Organizational Science (NAACSOS; now the Computational Social Science Society, CSSS), the European Social Simulation Association (ESSA), and the Pacific Asian Association for Agent-bBased Approach in Social Systems Sciences (PAAA)."

The evolution of systems in random media is a broad and fruitful field for the applica tions of different mathematical methods and theories. This evolution can be character ized by a semigroup property. In the abstract form, this property is given by a semigroup of operators in a normed vector (Banach) space. In the practically boundless variety of mathematical models of the evolutionary systems, we have chosen the semi-Markov ran dom evolutions as an object of our consideration. The definition of the evolutions of this type is based on rather simple initial assumptions. The random medium is described by the Markov renewal processes or by the semi Markov processes. The local characteristics of the system depend on the state of the ran dom medium. At the same time, the evolution of the system does not affect the medium. Hence, the semi-Markov random evolutions are described by two processes, namely, by the switching Markov renewal process, which describes the changes of the state of the external random medium, and by the switched process, i.e., by the semigroup of oper ators describing the evolution of the system in the semi-Markov random medium.

"Energy Methods in Dynamics "is a textbook based on the lectures given by the first author at Ruhr University Bochum, Germany. Its aim is to help students acquire both a good grasp of the first principles from which the governing equations can be derived, and the adequate mathematical methods for their solving. Its distinctive features, as seen from the title, lie in the systematic and intensive use of Hamilton's variational principle and its generalizations for deriving the governing equations of conservative and dissipative mechanical systems, and also in providing the direct variational-asymptotic analysis, whenever available, of the energy and dissipation for the solution of these equations. It demonstrates that many well-known methods in dynamics like those of Lindstedt-Poincare, Bogoliubov-Mitropolsky, Kolmogorov-Arnold-Moser (KAM), Wentzel Kramers Brillouin (WKB), and Whitham are derivable from this variational-asymptotic analysis.

This second edition includes the solutions to all exercises as well as some new materials concerning amplitude and slope modulations of nonlinear dispersive waves."

Current biological research demands the extensive use of sophisticated mathematical methods and computer-aided analysis of experiments and data. This highly interdisciplinary volume focuses on structural, dynamical and functional aspects of cellular systems and presents corresponding experiments and mathematical models. The book may serve as an introduction for biologists, mathematicians and physicists to key questions in cellular systems which can be studied with mathematical models. Recent model approaches are presented with applications in cellular metabolism, intra- and intercellular signaling, cellular mechanics, network dynamics and pattern formation. In addition, applied issues such as tumor cell growth, dynamics of the immune system and biotechnology are included.

Impulsive Control in Continuous and Discrete-Continuous Systems is an up-to-date introduction to the theory of impulsive control in nonlinear systems. This is a new branch of the Optimal Control Theory, which is tightly connected to the Theory of Hybrid Systems. The text introduces the reader to the interesting area of optimal control problems with discontinuous solutions, discussing the application of a new and effective method of discontinuous time-transformation. With a large number of examples, illustrations, and applied problems arising in the area of observation control, this book is excellent as a textbook or reference for a senior or graduate-level course on the subject, as well as a reference for researchers in related fields.

In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

In wntmg this monograph my aim has been to present a "geometric" approach to the structural synthesis of multivariable control systems that are linear, time-invariant and of finite dynamic order. The book is ad dressed to graduate students specializing in control, to engineering scientists involved in control systems research and development, and to mathemati cians interested in systems control theory. The label "geometric" in the title is applied for several reasons. First and obviously, the setting is linear state space and the mathematics chiefly linear algebra in abstract (geometric) style. The basic ideas are the familiar system concepts of controllability and observability, thought of as geometric prop erties of distinguished state subspaces. Indeed, the geometry was first brought in out of revulsion against the orgy of matrix manipulation which linear control theory mainly consisted of, around fifteen years ago. But secondly and of greater interest, the geometric setting rather quickly sug gested new methods of attacking synthesis which have proved to be intuitive and economical; they are also easily reduced to matrix arithmetic as soon as you want to compute. The essence of the "geometric" approach is just this: instead of looking directly for a feedback law (say u = Fx) which would solve your synthesis problem if a solution exists, first characterize solvability as a verifiable property of some constructible state subspace, say Y. Then, if all is well, you may calculate F from Y quite easily."