SAMPLED-DATA ROBOT ADAPTIVE-CONTROL WITH STABILIZING COMPENSATION

This article addresses the stability and performance of discretized ad aptive control algorithms for robotic manipulator control and the comp ensation of these algorithm,ns for improved stability and tracking per formance. The discretization of Slotine and Li's direct adaptive contr ol algorithm results in a sampled-data system for which stability has riot been guaranteed. By formulating the entire sampled-data system in continuous rime, Lyapunov's direct method is used to determine the st ability and to derive a nonlinear discrete-time compensating term. Thi s compensator is added to a multirate discretization of Slotine and LI S (1987a) adaptive algorithm, to stabilise the sampled-data system. Fo r sufficiently high gain, globally stable performance and a known boun d on the norm of the filtered error is proven. The stabilizing effect of the compensator and validity of the error bound predictions are dem onstrated through simulation and implementation of 2-DOF manipulator c ontrol.