Modeling and Control of Discrete Event Systems

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The goal of this research is to develop a mathematical theory for the analysis and control of discrete event systems (DES). DES arise in a variety of areas including, for example, multi-robot systems, manufacturing systems, data bases, distributed computing, pattern recognition, distributed and hierarchical optimization, and the higher level intelligent control of complex processes. The main thrust of the research is to develop a 'real-time' extension of supervisory control theory for DES. This will extend its scope by addressing two issues of great interest in applications: timing and performance. In addition, the research will expand upon and continue work on modular supervisor synthesis; distributed and hierarchical supervisors; structured controllers and aggregated models; the complexity of supervision, and forcing controls. The relationship of the supervisory control framework to other models (e.g., the max-algebra model, and stochastic models) will also be investigated with the aim of unifying, to some extent, the tools available for the study of discrete-event systems.