Open AccessArtificial Neural Network vs PID Controller for Magnetic Levitation System
Author(s) -
Gayani Karunasena,
H.D.N.S. Priyankara,
B.G.D.A. Madhusank
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20jul432
Subject(s) - pid controller , control theory (sociology) , levitation , artificial neural network , magnetic levitation , nonlinear system , controller (irrigation) , control system , control engineering , electromagnet , matlab , engineering , computer science , magnet , artificial intelligence , control (management) , physics , mechanical engineering , temperature control , electrical engineering , agronomy , quantum mechanics , biology , operating system
This research investigates the acceptability of the Artificial Neural Networks (ANN) over the PID Controller for the control of the Magnetic Levitation System (MLS). In the field of advanced control systems, this system identifies as a feedback-controlled, single input- single output (SISO) system. This SISO system used a PID controller for vertical trajectory controlling of a metal sphere in airspace by using an electromagnetic force that directed to upward. The vertical position of the metal sphere controlled according to the applied magnetic force generated by a powerful electromagnet and the electromagnetic force controlled by varying the supply voltage. To control this nonlinear system, we develop a multilayer artificial neural network by using Matlab software and integrate that with the physical magnetic levitation model. According to specific initial conditions, the actual responses of the magnetic levitation system with artificial neural network compares the desire response of the metal sphere. The ability of control this nonlinear system by using neural networks validate by comparing results obtained by the PID controller and artificial neural network.