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In recent years, there has been an increase in the use of Unmanned Aerial Systems (UAS) in the civilian sector for various purposes. As these platforms are constrained in terms of payload and capacity, they are typically equipped with a minimal sensor suite and the use of redundant sensors is uncommon. This research effort describes the design and simulation of a Neural Network (NN) based fault tolerant flight control approach for sensor and actuator failures, implemented on a parallel and distributed computational architecture. The inter process communication is implemented using BSD sockets and Message Passing Interface (MPI). For the purpose of the sensor failure detection, identification and accommodation (SFDIA) task, it is assumed that the pitch, roll and yaw rate gyros onboard the aircraft are without physical redundancy.