Decentralized Modular Approach for Fault Diagnosis of a Class of Hybrid Dynamic Systems: Application to a Multicellular Converter

Abstract

The majority of real systems are hybrid dynamic systems (HDS) in which the discrete and continuous dynamics cohabit. Their behavior can be described through a set of discrete operation modes and a set of analytical redundancy relations within each discrete mode. The fault diagnosis of HDS is based on the use of a global model. The latter can be too huge to be physically built for large-scale HDS with multiple discrete modes. Therefore, this paper proposes an approach to perform fault diagnosis of HDS, in particular discretely controlled continuous systems, without the use of a global model. In this approach, the system is divided into a set of discrete dynamic components. Then, the local models of the latter are enriched by adding the events generated by the abstraction of the continuous dynamics defined in each discrete mode. For each discrete component, a local diagnoser is constructed based on its enriched local model. Each local diagnoser is sensitive only to faults that impact the behavior (dynamics) of its associated component. Since the local diagnosers are constructed without the use of a global model but only the system discrete components’ local models, this approach scales well to large-scale systems with multiple discrete modes. A three-cell converter is used to illustrate the proposed approach.