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Quadratic programming algorithms for large-scale model predictive control
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DOI：10.1016/S0959-1524(02)00002-1.png)
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Quadratic programming (QP) methods tire an important element in the application of model predictive control (MPC). 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 (tip to two orders of magnitude) 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. (C) 2002 Elsevier Science Ltd. All rights reserved.
Keyword:
model predictive control
quadratic programming
cross-directional control
Schur complement methods
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