Dynamic modelling of a twin rotor system in hovering position

This paper investigates the utilisation of neural networks (NNs) and parametric linear approaches for modelling a twin rotor multi-input multi-output system (TRMS) in hovering position. A multi-layer perceptron (MLP) neuro-model is designed to characterise the TRMS. A parametric model of the system is then developed with the conventional recursive least square (RLS) technique. A comparative assessment of the two model types, in characterising the system, is carried out in the time and frequency domains. Experimental results demonstrate the superiority of the NN approach over the conventional linear modelling approach. The developed neuro-modelling approach will be used for control design and development in future work.