document: Quadratic programming algorithms for large-scale model predictive control Quadratic programming -LRB- QP -RRB- methods are an important element in the application of model predictive control -LRB- MPC -RRB- . As larger and more challenging MPC applications are considered , more attention needs to be focused on the construction and tailoring of efficient QP algorithms . In this study , we tailor and apply a new QP method , called QPSchur , to large MPC applications , such as cross directional control problems in paper machines . Written in C++ , QPSchur is an object oriented implementation of a novel dual space , Schur complement algorithm . We compare this approach to three widely applied QP algorithms and show that QPSchur is significantly more efficient -LRB- up to two orders of magnitude -RRB- than the other algorithms . In addition , detailed simulations are considered that demonstrate the importance of the flexible , object oriented construction of QPSchur , along with additional features for constraint handling , warm starts and partial solution
doc_bio_tags: B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B I I I O B I O O O O O B O O B I I O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O B I O B I O B I
extractive_keyphrases: quadratic programming algorithms qpschur cross directional control problems paper machines object oriented implementation simulations constraint handling warm starts partial solution
abstractive_keyphrases: large-scale model predictive control dual space schur complement algorithm flexible object oriented construction