FAT-based Adaptive Control for Flexible-joint Robots without Computation of the Regressor Matrix

An adaptive controller is presented in this paper to control an n-link flexible-joint manipulator with time-varying uncertainties. The function approximation technique (FAT) is utilized to represent time-varying uncertainties in some Unite combinations of orthogonal basis. The tedious computation of the regressor matrix needed in traditional adaptive control is avoided in the new design, and the controller does not require the variation bounds of time-varying uncertainties needed in traditional robust control. In addition, the joint acceleration is not needed in the controller realization. Via the Lyapunov-like stability theory, adaptive update laws are derived to give convergence of the output tracking error. A 2 DOF planar manipulator with flexible joints is used in the computer simulation to verify the effectiveness of the proposed controller.