AbstractDecision-making is an integral part of any consideration of the discipline of control Systems. This implies feedback of knowledge in some format, whether it is mediated via human or machineoriented methods. The application of AI methodologies to control Systems engineering is described in this review under two broad categories of design and implementation. The design of control strategies is itself divided into phases of modelling and simulation, identification, and algorithm selection and tuning. The aspects of implementation which are covered include real-time considerations such as knowledge-based control and fuzzy logic, multi-sensor data fusion, fault detection and Human–Computer Interaction (HCI).