This text is an extremely useful guide for those wishing to investigate the application of self-tuning control systems. The contents have been chosen in order to restrict the amount of theoretical detail to that necessary for explanation purposes, whilst application examples and programming suggestions are highlighted. The overall text is suitable for those wishing to gain the flavour of adaptive control, although those already familiar with selftuning techniques will find the problem solutions discussed to be most attractive. Parameter estimation, numerical solutions and software aspects are all considered at length, while simplified procedures and predictive self-tuning schemes are shown in terms of fundamental concepts.

This book provides an introduction to the techniques employed in the design and implementation of digital control systems. The text has arisen out of a highly successful IEE Vacation School held annually at Oxford University and the contents have been tailored to a digestible level and breadth by means of the feedback provided from previous School participants. As well as a tutorial approach to the description of basic concepts and general ideas used, most chapters include numerous worked examples and details of particular applications in order to enhance the theory introduced. The importance of putting over a technique by making use of practical examples is highlighted by the inclusion of several chapters in which selected case studies are presented detailing applications of both the more conventional and the more modern digital control ideas.

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.