Real-Time Implementation of a PD+DFNNS Controller for Compliance Robot

This paper presents the compliance control of a robot manipulator under a constrained environment. The controller design proposed herein is based on the intelligence adaptive control scheme. In this design, the DFNNs (dynamic fuzzy neural networks) and PD feedback controllers control the position and the contact force of robot end-effector. The DFNNs controller is employed to compensate for environmental variations such as payload mass and disturbance torque during the operation process; PD feedback controllers control the position and the contact force of end-effector. Applying these controllers allows us to adapt the manipulator to the unknown surface of the surrounding environment and to have close contact with the curved surface