Robust neural network controller design for a biaxial servo system

A robust contro1 method for synchronizing a biaxial servo system motion is proposed in this paper, A new neural network bascd cross-coupled control and neural network techniques arc used together to cancel out thc skew error. In the proposed control scheme, the conventional fixed gain PID cross-coupled controllcr (PIDCCC) is replaced with the neural network cross-coupled controllcr (NNCCC) to maintain biaxial servo system synchronization motion. In addition, neural network PID position velocity and velucity controllers provide the necessary control actions to maintain synehronization whilc following a variable command trajectory. This scheme provides strong robustness with respect to uncertain dynamics and nonlinearitics. The simulation results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.