Path tracking and obstacle avoidance for redundant robotic arms using fuzzy NMPC

Abstract

This paper presents a Nonlinear Model Predictive Control (NMPC) for redundant robotic arms. Using NMPC, the end-effector of robotic arm tracks a predefined geometry path in the Cartesian space in such a way that no collision with obstacles in the workspace and no singular configurations for robot occurs. Nonlinear dynamic of the robot including actuators dynamic is also considered. Moreover, the on-line tuning of the weights in NMPC is performed using the fuzzy logic. The proposed method automatically adjusts the weights in cost function in order to obtain good performance. Numerical simulations of a 4DOF redundant spatial manipulator actuated by DC servomotors shows effectiveness of the proposed method.