Study on Predictive Control for Trajectory Tracking of Robotic Manipulator

Abstract

Model predictive control (MPC) differs from other control methods mainly in implementation of the control actions. In this paper, the tracking error performance index of rolling optimization of predictive control is designed for a class of nonlinear systems by the relative degree, then employed to design controller for robot manipulator. In other words, the robot manipulator's reference trajectory is based on Taylor expansion, and the actual trajectory is substituted into the performance cost function which is derivated for minimum to obtain the controller. Then the performance analysis for the closed system is made. Simulation results demonstrate the effectiveness of the method based on Taylor expansion.