Double-neuro-sliding mode position control for direct drive turning table servo system based on genetic algorithms

Considering the parameters time variation, high nonlinear, disturbance and mechanical resonance of direct-drive turing table, a double neuro-sliding mode position control based on genetic algorithms is proposed. The turning table control system consists of sliding mode control and sliding swith control, the two control is used by two neural networks respectively, and use elastic BP algorithms and genetic algorithms (GA) to online optimize the weigh of the neural network. Simulation results demonstrate that the scheme can effectively achieve tracking performance and has strong robustness.