Parallel Processing in Digital Control is a volume to be published in the new Advances in Industrial Control series, edited by Professor M.J. Grimble and Dr. M.A. Johnson of the Industrial Control Unit, University of Strathclyde. The growing complexity of digital control systems in such areas as robotics, flight control and engine control has created a demand for faster and more reliable systems. This book examines how parallel processing can satisfy these requirements. Following a survey of parallel computer architectures, MIMD (Multiple Instruction Multiple Data) machines are identified as suitable systems for digital control problems, which are characterised by a mixture of regular and irregular algorithmic tasks. An example of a typical MIMD architecture, suitable for real-time control, (the Inmos Transputer) is introduced together with its associated parallel programming language (Occam). The key problem in implementing parallel software is associated with mapping parallel tasks onto physical processors. In this book a variety of schemes are described and assessed to help illustrate potential areas of difficulty for the real-time control software engineer. Solutions are proposed and tested on a flight control case study example. Recognising the widespread acceptance of MATLAB and its derivatives for computer aided control system design, this book demonstrates how mapping strategies can be realised in this environment and integrated with a transputer development system for on-line performance evaluation. A case study example demonstrates the power of this approach and important issues are highlighted. Readers will experience the advantages of parallel processing in digital control while being made aware of the key factors to be considered in the development of an effective solution. Practising control engineers and graduate/post-graduate students will find the book of particular interest and benefit.

This book introduces the advantages of parallel processing and details how to use it to deal with common signal processing and control algorithms. The text includes examples and end-of-chapter exercises, and case studies to put theoretical concepts into a practical context.

Over the past few years, the demand for high speed Digital Signal Proces sing (DSP) has increased dramatically. New applications in real-time image processing, satellite communications, radar signal processing, pattern recogni tion, and real-time signal detection and estimation require major improvements at several levels; algorithmic, architectural, and implementation. These perfor mance requirements can be achieved by employing parallel processing at all levels. Very Large Scale Integration (VLSI) technology supports and provides a good avenue for parallelism. Parallelism offers efficient sohitions to several problems which can arise in VLSI DSP architectures such as: 1. Intermediate data communication and routing: several DSP algorithms, such as FFT, involve excessive data routing and reordering. Parallelism is an efficient mechanism to minimize the silicon cost and speed up the pro cessing time of the intermediate middle stages. 2. Complex DSP applications: the required computation is almost doubled. Parallelism will allow two similar channels processing at the same time. The communication between the two channels has to be minimized. 3. Applicatilm specific systems: this emerging approach should achieve real-time performance in a cost-effective way. 4. Testability and fault tolerance: reliability has become a required feature in most of DSP systems. To achieve such property, the involved time overhead is significant. Parallelism may be the solution to maintain ac ceptable speed performance.

“A coherent and comprehensive account of all major aspects of parallel processing.” -- Back cover.