A grasping force control strategy is proposed in order to complete various fine manipulations by using anthropomorphic prosthetic hand. The position-based impedance control and force-tracking impedance control are used in free and constrained spaces, respectively. The fuzzy observer is adopted in transition in order to switch control mode, and a same position-based impedance controller is used in those two control modes. In order to achieve grasping force control, a reference force is added to the impedance controller in the constrained space. Trajectory tracking in free space and torque tracking in constrained space are realized, and reliability of mode switch and stability of system are achieved in transition. An adaptive sliding mode friction compensation method is proposed. The terminal sliding mode idea is used to design sliding mode function, which makes the tracking error converge to zero in finite time and avoids the problem of conventional sliding surface that the state tracking error can not converge to zero in finite time. Based on the characteristic of the exponential form friction, the sliding mode control law including the estimation of friction parameter is obtained through terminal sliding mode idea, and the on-line parameter update laws are obtained based on Lyapunov stability theorem. The experiments on the HIT prosthetic hand IV are carried out to evaluate the grasping force control strategy, and the experiment results verifies the effectiveness of this control strategy.
 Zhang T, Li K, Yang J. Seam tracking control for mobile welding robot based on vision sensor [J]. Journal of Central South University of Technology: English Edition, 2010, 17(6): 1320-1326.
 Seraji H, Colbaugh R. Force tracking in impedance control [C] //IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 1993: 499-506.
 Erickson D, Weber M, Sharf I. Contact stiffness and damping estimation for robotic systems [J]. International Journal of Robotics Research, 2003, 22(1): 41-57.
 Seraji H, Colbaugh R. Force tracking in impedance control [J]. International Journal of Robotics Research, 1997, 16(1): 97-117.
 Singh S K, Popa D O. An analysis of some fundamental problems in adaptive control of force and impedance behavior: Theory and experiments [J]. IEEE Transactions on Robotics and Automation, 1995, 11(6): 912-921.
 Love L J, Book W J. Environment estimation for enhanced impedance control [C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 1995: 1854-1859.
 Jung S, Hsia T C, Bonitz R G. Force tracking impedance control of robot manipulators under unknown environment [J]. IEEE Transactions on Control Systems Technology, 2004, 12(3): 474-483.
 Jung S, Hsia T C. Force tracking impedance control of robot manipulators for environment with damping [C]//33rd Annual Conference of the IEEE Industrial Electronics Society. Piscataway, NJ, USA: IEEE, 2007: 2742-2747.
 Jung S, Hsia T C. Neural network impedance force control of robot manipulator [J]. IEEE Transactions on Industrial Electronics, 1998, 45(3): 451-461.
 Jung S, Hsia T C. Reference compensation technique of neural force tracking impedance control for robot manipulators [C]//8th World Congress on Intelligent Control and Automation. Piscataway, NJ, USA: IEEE, 2010: 650-655.