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Recently, unmanned aerial vehicles (UAVs) have gained worldwide attention. Because the safety of people on board does not need to be considered, small UAVs can easily be made for low-cost. Therefore, a UAV can be used to observe disasters, to surveil for a long time, and so on. However, it also has several disadvantages such as unreliability and worse performance in unexpected situations. Because small UAVs must be easily made for lowcost, adding a redundant on-board actuator or sensor in order to deal with unexpected situations is unsuitable. Thus, several researchers have proposed a flight control system using a software redundancy approach. For fault detection, methods using multiple-model adaptive estimation (MMAE) (Guillaume Ducard & Hans P. Geering, 2008), and system parameters (Mohammad Azam et al, 2005) have been proposed. However, because these methods design a model or parameters for only each assumed fault in designing, unexpected faults cannot be detected. On the other hand, another method discriminates between faults and natural disturbances like gusts of wind. (Jovan D. Boskobic et al, 2005) However, this is not easy because the expected disturbances are assumed in designing. Currently, the demand for a UAV flight control system is to discriminate between faults and natural disturbances fundamentally with a simple algorithm. In this research, an intelligent flight control system was developed that can discriminate between faults and natural disturbances in order to evaluate and deal with the situation. In the proposed control system, an evaluator of flight conditions was designed on the basis of the dynamics of a controlled object. Moreover, to deal with the situation adaptively, a new flight-path-planning generator was introduced on the basis of the evaluation. In this study, each subsystem was designed by a neural network. Moreover, the learning-based systematical design method was developed that uses evaluation functions for the subsystems. To verify the effectiveness of the proposed flight control system, a six-degreeof-freedom nonlinear simulation was carried out.

Design of Intelligent Fault-Tolerant Flight Control System for Unmanned Aerial Vehicles