Because of nonlinearity, coupling, and friction of robot dynamic equations, it is hard to achieve high velocity motion maintaining the prescript accuracy through conventional PID control algorithm. So many dynamic control algorithms using robot dynamic equation have been proposed. One of them, Kawato's feedback error learning scheme requires neither an accurate model nor parameter estimation and makes the robot motion closer to the desired trajectory by repeating operation. In this thesis, the feedback error learning algorithm is implemented to control a robot system, 5 DOF revolute type Movemaster. For this purpose, an actuator dynamic model is constructed considering equivalent robot dynamic model with respect to actuator as well as friction model. The command input acquired from the actuator dynamic model is the sum of products of unknown parameters and known functions. To compute the control algorithm, a parallel processing computer, transputer, is used and real-time computing is achieved. The experiment is done for the three major link of Movemaster and its result is presented.
