A SELF-TUNING TORQUE FEEDBACK FOR CONTROL OF MANIPULATORS

Joint-torque sensory feedback (JTF) can achieve precise robot control through a relatively simple control implementation, if accurate measurements of joint torques are available. This paper presents the development of an adaptive JTF control law that requires only the incorporation of uncalibrated joint torque signals, i.e., the gains and offsets of the torque sensors are unknown. Also, all physical parameters of the joints including the inertia of the rotors, link twist angles, and friction parameters are assumed unknowns to the controller. The robot dynamics with JTF is presented in a standard form with minimum number of parameters, where the inertia matrix appears symmetric and positive definite. Simulation and experimental results are presented to demonstrate disturbance rejection and tracking performance of the proposed adaptive JTF controller.