Regressor-free adaptive fuzzy force tracking control of redundant robot manipulator for task space

In this study, an adaptive fuzzy force control of a redundant robot manipulator experiencing system uncertainties and operating in an unknown environment is proposed. This is important not only to provide additional control flexibility for complicated tasks but also to avoid the joint limit of a robot in implementing better dynamics and kinematics. The relation between the task and joint spaces is discussed to derive a dynamic model for force tracking controller design. To treat the system uncertainties, an adaptive fuzzy system approach is established to achieve the adaptive position and force controller design based on a regressor-free approach. Considering that the stiffness coefficient of the environment is assumed to be unknown, the gradient descent method is used to estimate this coefficient to achieve adaptive force tracking. A stability analysis of the closed-loop system and the corresponding update laws are given by the Lyapunov stability theorem. Finally, several apposite simulations using the KUKA lightweight robot are performed to validate our approach and demonstrate the performance and effectiveness of the proposed regressor-free adaptive fuzzy force controller.