Applications of stochastic techniques to partially observed discrete event systems

In order to address questions like fault diagnosis and optimization in large, complex systems, it is necessary to have a proper understanding of how information develops in such systems and what information is necessary in order to solve particular problems. Such a treatment of information is well developed in the theory of stochastic systems, but less so in the theory of discrete-event systems (DES). In this thesis we apply facets of stochastic systems theory to DES.; Three distinct major problems are considered. The first is the question of diagnosability of stochastic DES. The notions of A- and AA-diagnosability are defined for stochastic automata and conditions for A- and AA-diagnosability are determined through the construction of a stochastic diagnoser.; The second problem, the active acquisition of information problem, relates to how to optimally schedule measurements so as to minimize the observation cost necessary to control a system or diagnose a failure within it. A cost is incurred each instant a sensor is activated in an attempt to observe an event, and the objective is to minimize either the worst-case cost (for logical DES) or expected cost (stochastic DES) required in order to detect a failure. The solution of this problem requires properly defining an information state for DES and the construction of a proper sequence of information sigma-fields. Dynamic programming used the information sigma-fields to find an optimal solution.; The final problem concerns intrusion detection in centralized and decentralized supervisory control systems. The control action implemented by a supervisor may fail as a result of an intruder interfering with the system's performance and, as a result, strings that the supervisor wished to disable may be executed. Conditions for ensuring that all illegal strings can be disabled in the presence of intrusion are presented. A language measure technique is used to assess the potential damage an intruder can cause. Optimal control specifications are determined by constructing appropriate information states and using dynamic programming.