Knowledge representation and reasoning for flight control system based on weighted fuzzy Petri nets

To reach the high reliability of flight control software of unmanned aerial vehicle (UAV), it is required to design a fault diagnosis expert system in flight control system. Our main contribution to this work is in providing a fuzzy Petri Nets approach for modeling the fault diagnosis of flight control system. The systematic rule-based knowledge is obtained from human expertise and the fault diagnosis is opening, in which the reasoning rules can be updated and added anytime. The diagnosis result of the proposed the fault diagnosis of flight control system without human expert is consistent with the real result. It is shown that the fault diagnosis of flight control system is very effective and efficient.