Robotics applications, initially developed for industrial and manufacturing contexts, are now strongly present in several elds. Besides well-known space and high-technology applications, robotics for every day life and medical s- vices is becoming more and more popular. As an example, robotic manipu- tors are particularly useful in surgery and radiation treatments, they could be employed for civil demining, for helping disabled people, and ultimately for domestic tasks, entertainment and education. Such a kind of robotic app- cations require the integration of many di erent skills. Autonomous vehicles and mobile robots in general must be integrated with articulated manipu- tors. Many robotic technologies (sensors, actuators and computing systems) must be properly used with speci c technologies (localisation, planning and control technologies). The task of designing robots for these applications is a hard challenge: a speci c competence in each area is demanded, in the e ort of a truly integrated multidisciplinary design.

Illustrated with real-life manufacturing examples, Formal Methods in Manufacturing provides state-of-the-art solutions to common problems in manufacturing systems. Assuming some knowledge of discrete event systems theory, the book first delivers a detailed introduction to the most important formalisms used for the modeling, analysis, and control of manufacturing systems (including Petri nets, automata, and max-plus algebra), explaining the advantages of each formal method. It then employs the different formalisms to solve specific problems taken from today’s industrial world, such as modeling and simulation, supervisory control (including deadlock prevention) in a distributed and/or decentralized environment, performance evaluation (including scheduling and optimization), fault diagnosis and diagnosability analysis, and reconfiguration. Containing chapters written by leading experts in their respective fields, Formal Methods in Manufacturing helps researchers and application engineers handle fundamental principles and deal with typical quality goals in the design and operation of manufacturing systems.

The International Symposium on History of Machines and Mechanisms is a new initiative to promote explicitly researches and publications in the field of the History of TMM (Theory of Machines and Mechanisms). It was held at the University of Cassino, Italy, from 11 to 13 May 2000. The Symposium was devoted mainly to the technical aspects of historical developments and therefore it has been addressed mainly to the IFToMM Community. In fact, most the authors of the contributed papers are experts in TMM and related topics. This has been, indeed, a challenge: convincing technical experts to go further in-depth into the background of their topics of expertise. We have received a very positive response, as can be seen by the fact that these Proceedings contain contributions by authors from all around the world. We received about 50 papers, and after review about 40 papers were accepted for both presentation and publishing in the Proceedings. This means also that the History of TMM is of interest everywhere and, indeed, an in-depth knowledge of the past can be of great help in working on the present and in shaping the future with new ideas. I believe that a reader will take advantage of the papers in these Proceedings with further satisfaction and motivation for her or his work (historical or not). These papers cover the wide field of the History of Mechanical Engineering and particularly the History of TMM.

Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.

Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors.

The trusted handbook—now in a new edition This newly revised handbook presents a multifaceted view of systems engineering from process and systems management perspectives. It begins with a comprehensive introduction to the subject and provides a brief overview of the thirty-four chapters that follow. This introductory chapter is intended to serve as a "field guide" that indicates why, when, and how to use the material that follows in the handbook. Topical coverage includes: systems engineering life cycles and management; risk management; discovering system requirements; configuration management; cost management; total quality management; reliability, maintainability, and availability; concurrent engineering; standards in systems engineering; system architectures; systems design; systems integration; systematic measurements; human supervisory control; managing organizational and individual decision-making; systems reengineering; project planning; human systems integration; information technology and knowledge management; and more. The handbook is written and edited for systems engineers in industry and government, and to serve as a university reference handbook in systems engineering and management courses. By focusing on systems engineering processes and systems management, the editors have produced a long-lasting handbook that will make a difference in the design of systems of all types that are large in scale and/or scope.

This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.

Ever since fuzzy logic was introduced by Lotfi Zadeh in the mid-sixties and genetic algorithms by John Holland in the early seventies, these two fields widely been subjects of academic research the world over. During the last few years, they have been experiencing extremely rapid growth in the industrial world, where they have been shown to be very effective in solving real-world problems. These two substantial fields, together with neurocomputing techniques, are recognized as major parts of soft computing: a set of computing technologies already riding the waves of the next century to produce the human-centered intelligent systems of tomorrow; the collection of papers presented in this book shows the way. The book also contains an extensive bibliography on fuzzy logic and genetic algorithms.