A decentralized robust impedance control method of modular robot manipulators with physical human robot interaction

In this paper, an impedance control approach is presented for modular robot manipulator (MRM) system with physical human robot interaction (pHRI). Based on joint torque feedback (JTF) technique, the dynamic model of the manipulator systems is described as an integration of joint subsystems associated with the effect of interconnected dynamic coupling (IDC). The radial basis function neural network (RBFNN) has been employed to cope with of unknown human limb model. A dual closed-loop control framework of impedance control and decentralized robust control is proposed to deal with the force/position control problem. Based on Lyapunov theory, the tracking error of the closedloop robotic system is verified to be ultimately uniformly bounded (UUB). Finally, the effectiveness of the proposed method is verified by experiments.