Impedance Force / Position Control for Planar 3DOF Robot Manipulator by Fuzzy Neural Network Combination

As the demands for more robot's complex tasks were increased, force and torque control had become necessary. When contact forces are present, the performance of the trajectory tracking controller is degraded. Impedance force / position controller is proposed in this paper. The impedance force at the tip is controlled by fuzzy PID controller. PID controller tuned by adaptive linear network is used for trajectory tracking. A combination of fuzzy PID controller and PID controller tuned by neural network is used to generate the required torque at the robot manipulator's joints. The Jacobian matrix is derived for planar 3-DOF to transform the forces into joints' torque. Simulations are presented for robot manipulator with force contact at the tip. The trajectory tracking is improved by using fuzzy PID controller for impedance force of the environment.