Model-Based Diagnosis of Discrete Event Systems with an Incomplete System Model
Xiangfu Zhao, Ouyang Dantong · Frontiers in artificial intelligence and applications · 2008
Model-based diagnosis of discrete event systems (DESs) is more and more active in artificial intelligence. However, there has been always a very restrictive assumption in the previous works that the model of a given DES is complete, including all nominal behaviors and all possible failure behaviors of the system. In order to relax this so restrictive assumption, in this paper, model-based diagnosis of a DES with an incomplete system model is investigated. A new concept of “P-synchronization product” of finite state automata is proposed, by which the P-diagnosis of the DES with an incomplete system model is easily put forward. It is also shown that the traditional synchronization product of finite state automata can be seen as a special situation of P-synchronization product. In addition, an ideal heuristic way from theoretical view to improve the P-synchronization product is discussed as well.