Artificial Neural Network Control For Manipulators And Lyapunov Theory

: The paper presents a neural network controller design for trajectory tracking for manipulators. Lyapunov's stability theory was used to design the adaptive law for a computed torque method based artificial neural network controller. A joint space control scheme was used to test this type of controller. The controller was tested through simulation experiments and on the laboratory two D.O.F. SCARA mechanism. Keywords: manipulator, tracking control, artificial neural networks, Lyapunov function 1. INTRODUCTION Advanced manufacturing processes require ever greater accuracy and speed of performed smooth movements. Positioning tasks of robot mechanisms represent quite a difficult problem, which is due to great nonlinearities and influences of coupling in robot joints. Control tasks can be efficiently performed if advanced control schemes are used because manipulators are subjected to structured and unstructured uncertainties in all industrial applications. Structured uncertainty is defin..