Recently, there has been a significant increase in the use of techniques from applied Artificial Intelligence (AI) such as expert systems to implement the control functions for complex industrial processes. The research funded is showing that the design of such expert controllers (controllers implemented via expert systems) can be accomplished using the same design philosophy as that used for fuzzy controllers. Moreover, to ensure that such expert controllers can be trusted in critical environments (e.g., aircraft control, spacecraft control, process control) this research is developing a discrete event system (DES) theoretic framework for the modeling and analysis of expert control systems. In particular, a mathematical model is introduced that can represent "rule-based" expert systems and a wide class of processes. Techniques from DES theory are being developed for the analysis of reachability (to study inference chains), cyclic behavior (to verify that the expert system will not get stuck in circular reasoning), and stability properties (to verify critical properties related to the safe operation of expert control systems). The application of the approach to the solution of a load balancing problem in flexible manufacturing systems and process control problems is being investigated. Moreover, implementation issues for expert controllers are being investigated via the implementation of an expert controller for a flexible link manipulator.//
