Trajectory Tracking Control of a Parallel Drive Manipulator Based on Model Free Adaptive Control

In this paper, a data-driven model-free adaptive control design is proposed for a parallel drive manipulator. The manipulator dynamic system is transformed into an equivalent dynamic linearization data model using pseudo partitioned jacobian matrix. The control law is designed based on the equivalent dynamic linearization data model. The main feature of the proposed control design is that the controller design depends only on the measured input and output data of the manipulator, without using any model information. More specifically, only the motor voltages and joint angle information are used in the closed-loop control system. Stability analysis is presented. Experiments are conducted to verify the effectiveness of the proposed control design.