02285nam a2200193Ia 4500999001700000100001200017100007400029245010200103260001400205260001000219260000900229300000700238500154400245700008501789856002601874942001101900952009001911952009002001  c57760d57757  a14MPE09  aSara Hafeez Rajput a14MPE09aSupervisor Prof. Dr. Aslam Pervez Memon 0aApplication Of Artificial Neural Network in The Performance of Non Linear Twin Rotor Mimo System   aNawabshah  bQUEST  c2017  a64  aABASTRACT

The control and modeling of flexible maneuvering system, such as helicopter unmanned   vehicles   has   always   been   a   challenging   problem   due   to-linearity, significant cross-coupling between its two, complex aerodynamics force between its two rotors and the of some of its states and outputs for measurements.  Helicopter has been widely used in air traffic systems, such as traffic condition assessment, prevention and   crime precautions. The twin rotor multiple input multiple output system (TRMS) is a laboratory setup which    resemble	the behavior   of   a helicopter   in   certain   aspects   due to   the complicated nonlinearity and high cross coupling effect between main rotor and tail rotor   like helicopter.   Some of its inputs   and   outputs   are inaccessible   for  the measurement. The control effort is to make the beam of TRMS to move quickly and accurately to the desired attitudes both in terms of pitch angle and azimuth angle under decoupling effects between two axes. The project is aimed at devising a model of the non-linear MIMO system by using Neural Networks.  This is because of the efficient modeling approach provided by neural networks highly non-non-linear systems.  The mathematical modeling of TRMS is done using MATLAB/Simulink. The simulation results are compared with the results of conventional PID controller.
The results of A (MLP & (RBF) show better transient, rise time, overshoot and steady state response as compared to conventional PID controller.

















  aDepartment of Master Engineering in Power Engineering Of Electrical Engineering   uhttp://tiny.cc/cs2cvz  cTHESIS  00104070aRESEARCHbRESEARCHd2018-05-16l0pMP/17-168r2018-05-16 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2018-10-08l0pMP/30-340r2018-10-08 00:00:00yTHESIS