Numerical Methods for Solution of the Extended Linear Quadratic Control Problem
Publication: Research - peer-review › Article in proceedings – Annual report year: 2012
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Numerical Methods for Solution of the Extended Linear Quadratic Control Problem. / Jørgensen, John Bagterp; Frison, Gianluca ; Gade-Nielsen, Nicolai Fog; Dammann, Bernd.
In: Nonlinear Model Predictive Control. Vol. 4 International Federation of Automatic Control, 2012. p. 187-193 (IFAC Proceedings Volumes (IFAC-PapersOnline) ).Publication: Research - peer-review › Article in proceedings – Annual report year: 2012
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TY - GEN
T1 - Numerical Methods for Solution of the Extended Linear Quadratic Control Problem
A1 - Jørgensen,John Bagterp
A1 - Frison,Gianluca
A1 - Gade-Nielsen,Nicolai Fog
A1 - Dammann,Bernd
AU - Jørgensen,John Bagterp
AU - Frison,Gianluca
AU - Gade-Nielsen,Nicolai Fog
AU - Dammann,Bernd
PB - International Federation of Automatic Control
PY - 2012
Y1 - 2012
N2 - In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples.
AB - In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples.
U2 - 10.3182/20120823-5-NL-3013.00092
DO - 10.3182/20120823-5-NL-3013.00092
SN - 978-3-902823-07-6
VL - 4
BT - Nonlinear Model Predictive Control
T2 - Nonlinear Model Predictive Control
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
T3 - en_GB
SP - 187
EP - 193
ER -