Hybrid force and position control of robotic manipulators using passivity backstepping neural networks

Abstract

This paper presents a method of force/position control by using the backstepping and passivity strict-feedback neural networks technique; passivity monitor can evaluate stability of a system based on the concept of passivity. The parameters estimation for the design is made by the neural networks technology, using the decouple method and matrix transforming technology, decomposing the robot system as the position subsystem and the force subsystem, then the control law of these subsystems are designed respectively. The results obtained are satisfactory by using hybrid force and position control, the error is negligible and the global stability of the system can also be obtained. © Springer-Verlag Berlin Heidelberg 2007.