Self-learning PID Control for X-Y NC Position Table with Uncertainty Base on Neural Network

Hu Xiaoping (Lishui University)
Wang Chao (Lishui University)
Zhang Wenhui (Lishui University)
Ma Jing (Lishui University)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 12, No 2: June 2014

An adaptive radical basis function (RBF) neural network PID control scheme for X-Y position table is proposed by the paper. Firstly, X-Y position table model is established, controller based on neutral network is used to learn adaptive and compensate uncertainty model of X-Y position table, neutral network is used to study model. PID neural network controller base on augmented variable method is designed. PID controller is used as assistant direction error controller, neural network parameters base on stochastic gradient algorithm can be adjust adaptive on line. The simulation results show that the presented controller has important engineering value.