Control of a two-DOF parallel robot with unknown parameters using a novel robust adaptive approach

Model-based methods lose their performance in confronting with model uncertainties and disturbances. Accordingly, some degrees of adaptation to the involved conditions are required. In this paper, a novel robust adaptive scheme is proposed which guarantees the simultaneous identification and control of a system in the presence of external disturbances. Thereafter, the suggested algorithm is implemented on a 2-DOf spherical parallel robot as a stabilizer device. By identifying unknown parameters of Jacobian matrix, the relative identification error is obtained as 0.0207. Applying external excitations to the base, the ratio of end-effector to base orientation is acquired as 0.091, demonstrating proper stabilization in comparison with other two well-known methods. The proposed structure also reveals a reliable performance in tracking desired paths for the end-effector Euler angles.