One of the most promising application areas for expert systems is an on-line advisor to a process plant operator. In modern control rooms, the operator is responsible for monitoring thousands of measurements and interpreting plant condition. The expert system design for this application required new approaches toward the creation of knowledge bases, the real-time use of knowledge for inference and other requirements. Expert systems have been applied in several plants to assist the operator in this task. The design and implementation issues are reviewed. The extension of this work to non-process applications which have similar real-time requirements is currently proceeding.

A type of intelligent control system which can emulate the reasoning procedures of a human expert in order to generate the necessary control action. Expert control systems seek to incorporate knowledge about control system design, practical operations, and abnormal system recovery plans to automate tasks normally performed by experienced control engineers (the experts). Techniques relating to the field of artificial intelligence are usually used for the purpose of acquiring and representing knowledge and for generating control decisions through an appropriate reasoning mechanism. As it operates essentially on a knowledge base, an expert control system is often referred to as a knowledge-based control system. One of the most important benefits associated with the use of an expert control system is the inherent capability of the system to deal with uncertainty in information. Information provided to these systems need not be complete or precise. It can be general, qualitative, or vague. These properties do not cause difficulty because, like humans, expert control systems possess functionalities to perceive, reason, infer, and deduce new information. They can learn, gain new knowledge, and improve their performance through experience.