Fault-Tolerant Supervisory Control

Abstract

In this thesis, we investigate the problem of fault tolerance in the framework of discrete-event systems (DES). We introduce our setting, and then provide a set of fault-tolerant definitions designed to capture different types of fault scenarios and to ensure that our system remains controllable and nonblocking in each scenario. This is a passive approach that relies upon inherent redundancy in the system being controlled, and focuses on the intermittent occurrence of faults. Our approach provides an easy method for users to add fault events to a system model and is based on user designed supervisors and verification. As synthesis algorithms have higher complexity than verification algorithms, our approach should be applicable to larger systems than existing active fault-recovery methods that are synthesis based. Also, modular supervisors are typically easier to understand and implement than the results of synthesis. Finally, our approach does not require expensive (in terms of algorithm complexity) fault diagnosers to work. Diagnosers are, however, required by existing methods to know when to switch to a recovery supervisor. As a result, the response time of diagnosers is not an issue for us. Our supervisors are designed to handle the original and the faulted system. In this thesis, we next present algorithms to verify these properties followed by complexity analyses and correctness proofs of the algorithms. Finally, examples are provided to illustrate our approach. In the above framework, permanent faults can be modelled, but the current method was onerous. To address this, we then introduce a new modeling approach for permanent faults that is easy to use, as well as a set of new permanent fault-tolerant definitions. These definitions are designed to capture several types of permanent fault scenarios and to ensure that our system remains controllable and nonblocking in each scenario. New definitions and scenarios were required as the previous ones were incompatible with the new permanent fault modeling approach. We then present algorithms to verify these properties followed by complexity analyses and correctness proofs of the algorithms. An example is then provided to illustrate our approach. Finally, we extend the above intermittent and permanent fault-tolerant approach to the timed DES setting. As before, we introduced new fault-tolerant properties and algorithms. We then provide complexity analyses and correctness proofs for the algorithms. An example is then provided to illustrate our approach.