Robust Adaptive Control of Robot Manipulator Using General Regression Neural Network

Authors:

Jyoti Ohri (National Institute of Technology, Kurukshetra)

Sourav Dutta (National Institute of Technology, Kurukshetra)

Keywords: Robust, adaptive, neural network, sliding mode, control, uncertain robot manipulator.

Abstract:

In this paper a robust adaptive neural network sliding mode controller for robotic manipulators with uncertain load is presented. The proposed approach remedies the previous problems met in practical implementation of classical sliding mode controllers. An adaptive General Regression Neural Network (GRNN) is used to calculate each element of the control gain vector; discontinuous part of control signal, in a classical sliding mode controller. The key feature of this scheme is that prior knowledge of the system uncertainties is not required to guarantee the stability. Also the chattering phenomenon is completely eliminated. To demonstrate the effectiveness of the proposed approach, a three link SCARA robot is simulated in the presence of uncertainties.