Hybrid parallel neuro-controller for multirotor unmanned aerial vehicle

This paper provides a new method of building a flight control system for multirotor unmanned aerial vehicle based on hybrid parallel neuro-controller that uses radial basis function artificial neural network. Activation functions of hidden layer neurons are optimized in a way that allows for online training. We show that proposed hybrid neuro-controller is more effective than traditional manually configured PID controller.