A finite state machine based diagnostic expert system of large-scale autonomous unmanned submarine

Abstract

Fault diagnosis and decision have received a lot of theoretical and practical attention over the last years. This paper aims at the design of efficient and reliable security assurance of Large-scale autonomous unmanned submarine (L-AUS). Firstly, this paper analyzes the control objective, then models an on-line diagnostic expert system with an inference engine based on a finite state machine. Finally, this paper verifies the effectiveness of this expert system and reasoning machine by physical simulation. This paper proposes a high-efficiency reasoning machine which can cope with the complex fault diagnostic logic of L-AUS. The finite state machine also offers the possibility to model emergency system of L-AUS and to test a reaction system by tracking the logic flow during simulations.