EXPERIMENTAL EVALUATION OF NONLINEAR ADAPTIVE CONTROLLERS

Attractive methods for learning the dynamics and improving the control of robot manipulators during movements have been proposed for more th an 10 years, but they still await applications. This article investiga tes practical issues for the implementation of these methods. Two nonl inear adaptive controllers, selected for their simplicity and efficien cy, are tested on 2-DOF and 3-DOF manipulators. The experimental resul ts show that the Adaptive FeedForward Controller (AFFC) is well suited for learning the parameters of the dynamic equation, even in the pres ence of friction and noise. The control performance along the learning trajectory and other test trajectories are also better than when meas ured parameters are used, However, when the task consists of driving a repeated trajectory, the adaptive lookup table MEMory is simpler to i mplement, It also provides a robust and stable control, and results in even better performance.