Title :
Intelligent position control of earth station antennas with model independent friction compensation based on MLP neural networks
Author :
Razi, Amir ; Menhaj, Mohammad Bagher
Author_Institution :
Dept. of Electr. Eng., Amir Kabir Univ. of Technol., Tehran, Iran
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 friction is not necessary to be measured or identified for considering in the controller designing using this method. However due to test of the proposed method performance, this nonlinearity term modeled by a dead zone block. Simulation results show the effectiveness of T.M.L. method for robust control in the presence of friction nonlinearity.
Keywords :
compensation; control nonlinearities; delays; multilayer perceptrons; neurocontrollers; position control; robust control; satellite antennas; satellite tracking; Earth station antenna; LEO satellite tracking; Low Earth Orbit satellite tracking; MLP neural network; controller design; dead zone block; friction nonlinearity; intelligent position control; model independent friction compensation; multilayer neural network; nonlinearity term; robust control; through model lemma; Friction; Integrated circuit modeling; Intelligent control; Intelligent networks; Low earth orbit satellites; Multi-layer neural network; Neural networks; Position control; Satellite antennas; Satellite ground stations; Coulomb and viscous friction; Earth station antenna; Intelligent Control; LEO Satellites; T.M.L. Method;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5244946
