Dynamic neural network control of hydraulic parallel robot

Aimed at the problems of time varying parameters and large load disturbance in cylinders servo system of hydraulic-driven parallel robot, a new dynamic neural network was designed by means of adding feedback loops to feedforward network, and the intelligent controller based on this dynamic network was employed to control the cylinder servo system. The network learning algorithm was deduced according to the new integrative objective function that evaluated system performance perfectly. The experimental results show that the controller design is independent upon system model, and the controller has self-adaptability to time varying parameters and robustness to large load disturbance with the satisfactory static and dynamic performance.