Artificial Intelligence In Real Time Control 1992

The symposium had two main aims, to investigate the state-of-the-art in the application of artificial intelligence techniques in real-time control, and to bring together control system specialists, artificial intelligence specialists and end-users. Many professional engineers working in industry feel that the gap between theory and practice in applying control and systems theory is widening, despite efforts to develop control algorithms. Papers presented at the meeting ranged from the theoretical aspects to the practical applications of artificial intelligence in real-time control. Themes were: the methodology of artificial intelligence techniques in control engineering; the application of artificial intelligence techniques in different areas of control; and hardware and software requirements. This symposium showed that there exist alternative possibilities for control based on artificial intelligence techniques.

This set of proceedings contains the most significant papers presented at the third IFAC Workshop on Artificial Intelligence in Real-time Control, which was held from September 23-25, 1991 in the USA. In this workshop, although there were still some "exotic" applications, a more practical view of the applications and limitations of current AI technology dominated the participants' discussions. With its resultant focus on reliability and safety considerations, the workshop posed as many questions as it answered. It provides an excellent mirror of the current state-of-the-art which these proceedings are intended to illustrate.

Artificial Intelligence is one of the new technologies that has contributed to the successful development and implementation of powerful and friendly control systems. These systems are more attractive to end-users shortening the gap between control theory applications. The IFAC Symposia on Artificial Intelligence in Real Time Control provides the forum to exchange ideas and results among the leading researchers and practitioners in the field. This publication brings together the papers presented at the latest in the series and provides a key evaluation of present and future developments of Artificial Intelligence in Real Time Control system technologies.

Hardbound. The symposium had two main aims, to investigate the state-of-the-art in the application of artificial intelligence techniques in real-time control, and to bring together control system specialists, artificial intelligence specialists and end-users. Many professional engineers working in industry feel that the gap between theory and practice in applying control and systems theory is widening, despite efforts to develop control algorithms. Papers presented at the meeting ranged from the theoretical aspects to the practical applications of artificial intelligence in real-time control. Themes were: the methodology of artificial intelligence techniques in control engineering; the application of artificial intelligence techniques in different areas of control; and hardware and software requirements. This symposium showed that there exist alternative possibilities for control based on artificial intelligence techniques.

Computer scientists have long appreciated that the relationship between algorithms and architecture is crucial. Broadly speaking the more specialized the architecture is to a particular algorithm then the more efficient will be the computation. The penalty is that the architecture will become useless for computing anything other than that algorithm. This message holds for the algorithms used in real-time automatic control as much as any other field. These Proceedings will provide researchers in this field with a useful up-to-date reference source of recent developments.

This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.