Transputer based trajectory tracking neural network controller for a robot mechanism

摘要

The paper presents a neural network controller for trajectory tracking for a two D.O.F. SCARA robot mechanism. Two types of neural network controllers were built: a joint space neural network controller and a task space neural network controller. The two controllers were compared with a computed torque method controller in a joint as well as task space. The four controllers were tested on a real robot mechanism. The Lyapunov theory for deriving the adaptation law, or the learning algorithm of neural networks, was used to prove the robot system stability with a neural network controller.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>