Position control of a translational manipulator using a robust nonlinear predictive control

Abstract

Summary form only given: This paper deals with the design of a position control system using a robust nonlinear model predictive controller, which is employed to control simultaneously car and arm positions of a translational manipulator of 2DOF (2 Degrees of Freedom). The control law is based on prediction model and is derived starting from the prediction of the output: a truncated Taylor series expansion of order two. A simple speed observer is employed to estimate positions derivatives. The design of the predictive control system requires the derivation of the dynamic nonlinear model of the translational manipulator and the determination of the corresponding control law. Intensive simulation studies were performed to verify that the outputs of the designed control system, car and arm positions, follow arbitrary step wise reference trajectories satisfying the design specifications previously established.