This paper presents a survey of the potential use of Genetic Algorithms (GAs) for process control. GAs are a family of iterative search algorithms based on an analogy with the process of natural selection and evolutionary genetic. Application to off-line control is first envisaged, where GAs are used for task scheduling, calculation of optimal set points and design of optimal control strategies. Then application to on-line control is considered, focusing on system identification and enhancement of existing controllers, two problems for which GAs seem to offer the most promising results. After the description of possible applications of GAs to supervisory problem, the general advantages, drawbacks and limitations of applying GAs to process control are discussed, and further lines of research are drawn.
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