Rahideh - School of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, I.R.IRAN, Department of Engineering, Queen Mary, University of London, London E ۱ ۴NS, UK
Safavi - School of Engineering, Shiraz University, Shiraz, ۱.R.IRAN
Shaheed - Department of Engineering, Queen Mary, University of London, London E ۱ ۴NS, UK

A nonlinear dynamic modelling approach based on neural network (NN) for a real Twin Rotor hIlM0 System (TlbMS), in terms of its 2 degree of freedom (DOF) dynamics, is presented in this paper. The TRMS is a highly nonlinear system with signiJicant cross-coupling between its horizontal and vertical axes. It is perceived as an aerodynamic test rig representing the control challenges of modern air vehicles. Accurate dynamic modelling is a prerequisite to address such challenges satisfactorily. A feedforward neural network has been trained using Scaled Conjugate Gradient (SCG) learning algorithm. The trained NN based models have been tested with a set of data that are difeerent from those used for trainingpurpose. For more validation the power spectral densiv (PSD) of the model is compared with that of the real TRhfS and also the correlation validations of the test results are presented in order to show the eflectiveness ofthe proposed model. The results show that the developed model can adequately represent the highly nonlinear features ofthe system

Neural networks, dynamic modelling, TRMS, scaled conjugate gradient