Closing the Loop – Predictive Lifted Newton Trajectory Tracking Algorithm

Abstract

This paper introduces a predictive closed-loop trajectory tracking algorithm for nonlinear control systems that combines the Model Predictive Control (MPC) approach with the task priority Lifted Newton method. The optimal control problem within MPC is replaced by the open-loop trajectory tracking problem formulated as a constrained motion planning problem. Constraints reflect the distance in the task space between the system current output and the desired trajectory. The original constrained motion planning problem is replaced by an unconstrained one addressed in an extended control system representation, and solved with the task priority version of the Lifted Newton method. All other steps of the MPC scheme remains unchanged. Performance of the closed-loop predictive Lifted Newton trajectory tracking algorithm has been demonstrated with series of computer simulations for the kinematic car type platform.