Architectures and techniques of artificial intelligence in process control

Abstract

Artificial Intelligence has been applied in process control, using a range of AI techniques, such as rules, fuzzy logic and neural nets, and architectures, including blackboards, layered architectures and, most recently, distributed and multi-agent architectures. In the early days, expert systems in process control were seen as a way of possibly removing the operator from the control loop. But as applications have become more complex and the processes are becoming managed rather than merely controlled, the role of the operator has changed. It was never possible to define permanently the operator's role when supported by an intelligent machine, so now are we are seeing the emergence of negotiation and dialogue between operator and machine for dynamic allocation of control tasks?