Neural network disturbance observer based controller of an electrically driven stewart platform using backstepping for active vibration isolation

In this paper, a radial basis function disturbance observer (RBFDO) based controller is developed to solve the control problem of an electrically driven Stewart platform for multiple degree-of-freedom (DOF) active vibration isolation. The RBFDO´s are employed to monitor the modeling errors and external disturbances, etc. And on-line tuning rules for updating the weights of the RBFDO´s are designed based on the e1-modification algorithm. Meanwhile, by considering the dynamics of the Stewart platform and its voice coil actuators, the developed RBFDO´s are integrated with the backstepping method to design the active vibration isolation controller. In the presence of external vibrations and model uncertainties, the uniformly ultimately boundedness of the stabilization errors and the weight estimation errors can be guaranteed by the Lyapunov theory. Finally, simulation results demonstrate the proposed controller can effectively attenuate external low-frequency vibrations in six DOFs.