Identification and nonlinear control of a ball-plate system using neural networks

Abstract

This paper studies neural networks in order to identify and control the traditional ball-plate problem. Firstly, a nonlinear model of ball and plate system consisting of two parts is established. Secondly, a multilayer perceptron neural network is employed to identify the plant. Next, a feedback controller is designed based on neural network method to control the system. Eventually, simulations are accomplished via Matlab/Simulink and results show the remarkable ability of identifier and effectiveness of the proposed neural network-based controller.