Artificial Neural Network Control of a Magnetic Levitation System Mustapha Muhammad

Magnetic levitation (maglev) systems are nowadays employed in applications ranging from non-contact bearings and vibration isolations of sensitive machinery to high-speed passenger trains. In this work a mathematical model of a laboratory maglev system was derived using Lagrangian approach. Three controllers were designed for the maglev system and their performances were investigated via simulation using Simulink. Firstly, a pole-placement controller was designed on the basis of specifications on peak overshoot and settling time. Secondly, a nonlinear state feedback linearization control scheme was designed. Finally a 3-layer feed-forward artificial neural network (ANN) controller comprising 3-input nodes, a 5-neuron hidden layer and 1-neuron output layer was trained using the linear state feedback controller with a random reference signal. The robustness of the three control schemes was investigated with respect to parameter variations and reference step input magnitude variations.... Это и многое другое вы найдете в книге Artificial Neural Network Control of a Magnetic Levitation System (Mustapha Muhammad)