An approach to adaptive neural control of robot manipulators

Abstract

An adaptive neural control scheme for mechanical manipulators is presented. The neural design has been developed basically following adaptive control design principles and taking into account a number of properties that adaptive schemes and neural controllers have in common. The control loop essentially consists of a neural network for learning the robot's inverse dynamics and online generation of the control signal. Some simulation results are provided to evaluate the design.