Adaptive Control of Robot Manipulators With Uncertain Variable Parameters

The control of robot manipulators has become a hot topic in these years. With increasing usage of robots in military industry, manufacturing, service industry and daily entertainments for common people, there is an increasing need to design robots with higher performance and various functions. Adaptive control is powerful in solving control problems with uncertainties, and thus become a potent tool in this area. This thesis studies the adaptive control of robot manipulator systems with uncertain and time-varying parameters. A new parametrization scheme is derived to expand the capacity of adaptive control in dealing with such parameter uncertainties. Unlike the existing control methods, each parameter is not estimated by a single estimate, but a group of estimates, which can help robot manipulators perform better in time-varying environments. This control algorithm can guarantee stability and asymptotic tracking ability, despite large and persistent uncertain parameter variations. Compared with classical control methods, the new adaptive control designs will help reduce the effect of the uncertainties of time-varying parameters in the robot working process. Simulation results of control for a planar elbow manipulator, a typical type of robot manipulators, are presented to verify our control performance.