RBF neural network control on electro-hydraulic load simulator

A new control structure for load simulator to improve its performance is presented, in which there are three RBF neural networks. One is taken as NN PID controller, the second as compensator for adjusting anti-disturbance coefficient dynamically, and the third is used for identifying the plant (NNI). The neural network PID controller is designed to overcome the shortcoming of the only neural network controller. A RBF neural network is used to identify the plant, in which the Jacobian matrix is used for adjusting disturbance-reduced parameter in the compensating neural network. The simulation and experiment are carried out, which show a good result. This method is of validity and robustness.