Variant Predictor-Corrector Method for Linear Predictive Control Using Modified Uzawa Algorithm

Tianchen Liu, Kushal Chakrabarti, Nikhil Chopra

Abstract: In this paper, a new variant of the predictorcorrector interior point method (IPM) pipeline is proposed for model predictive control (MPC) problems for linear time-invariant systems, which can be reformulated as quadratic programming (QP) problems. At each iteration in the IPM, finding the search direction via solving a linear system of equations is usually the step with the highest computational cost. A modified Uzawa algorithm is developed to improve the performance in the proposed IPM, which can address the ill-conditioning issue at the late iterations and reduce computational cost. Results of an MPC problem example are presented to show the performance of the proposed pipeline.