A Regularized and Smoothed Fischer–Burmeister Method for Quadratic Programming With Applications to Model Predictive Control

摘要

This paper considers solving convex quadratic programs in a real-time setting using a regularized and smoothed Fischer–Burmeister method (FBRS). The Fischer–Burmeister function is used to map the optimality conditions of a quadratic program to a nonlinear