The 6th IFAC Workshop on Algorithms and Architectures for Real-Time Control (AARTC'2000) was held at Palma de Mallorca, Spain. The objective, as in previous editions, was to show the state-of-the-art and to present new developments and research results in software and hardware for real-time control, as well as to bring together researchers, developers and practitioners, both from the academic and the industrial world.

The AARTC'2000 Technical Program consisted of 11 presented sessions, covering the major areas of software, hardware and applications for real-time control. In particular, sessions adressed robotics, embedded systems, modeling and control, fuzzy logic methods, industrial process control and manufacturing systems, neural networks, parallel and distributed processing, processor architectures for control, software design tools and methodologies, and SCADA and multi-layer control. A total of 38 papers were selected from high-quality full draft papers and late breaking paper contributions (consisting of extended abstracts). Participants from 15 countries attended the AARTC'2000 workshop.

The technical program also included two plenary talks given by leading experts in the field. Roger Goodall (Department of Electronic and Electrical Engineering, Loughborough University, UK) presented "Perspectives on processing for real-time control," and Ricardo Sanz (Universidad Politecnica de Madrid, Spain), focused on "CORBA for Control Systems." Another highlight in the program was the final session on industrial presentations which was held in common with the Workshop on Real-Time Programming (WRTP'2000). In this session, Abel Jimenez (Industria de Turbo Propulsores S. A., Spain) presented the "Thrust Vectoring System Control Concept," Ulrich Schmid (Technische Universitat Wien, Austria) made a presentation with the title "Applied Research: A Scientist's Perspective," and Harold W. Lawson (Lawson Konsult AB, Sweden) addressed "Systems Engineering of a Successful Train Control System."

Neural networks are an exciting technology of growing importance in real industrial situations, particularly in control and systems. This book aims to give a detailed appreciation of the use of neural nets in these applications; it is aimed particularly at those with a control or systems background who wish to gain an insight into the technology in the context of real applications. The book introduces a wide variety of network types, including Kohenen nets, n-tuple nets and radial basis function networks, as well as the more usual multi-layer perception back-propagation networks. It begins by describing the basic principles and some essential design features, then goes on to examine in depth several application studies illustrating a range of advanced approaches to the topic.