Robust robot control enhanced by a hierarchical adaptive fuzzy algorithm

Robust control of robots including motor dynamics is considered based on a dynamic game approach. The control law is composed of three main components. The first component utilizes feedback linearization to cancel the system's nominal nonlinearity and achieve tracking via pole-placement. The discrepancy between the nominal functions used in feedback linearization and the true ones is compensated for using the second control component that is based on an adaptive hierarchical fuzzy algorithm. The third control component ensures robustness by attenuating the worst-case effect of both the residue due to fuzzy cancellation and the external disturbances. The main contribution of this work is the derivation of the hierarchical adaptive fuzzy algorithm to avoid the rule explosion phenomenon that characterizes traditional fuzzy systems. We also prove that the proposed control algorithm is locally stable. Simulation of a two-link manipulator illustrates a successful performance of our controller and investigates the effect of the design parameters. (C) 2004 Elsevier Ltd. All rights reserved.