Intelligent position control of earth station antennas with backlash compensation based on MLP neural network

Abstract

An Intelligent Control (IC) method based on MLP neural networks and Through Model Lemma (T.M.L.) is implemented to control the position of a Low Earth Orbit (LEO) satellites tracking earth station antenna. This approach relies on two different multilayer neural networks with delayed inputs, for the purpose of identification and control. Nonlinear term in motors caused by gear-box gaps or other parts lameness is not necessary to be measured or identified for considering in controller designing using this method. However due to test of the proposed method performance, this nonlinearity term modeled by a backlash block. Simulation results show the effectiveness of T.M.L. method for robust control in the presence of backlash nonlinearity.