## Numerical Methods for Solution of the Extended Linear Quadratic Control Problem

Publication: Research - peer-review › Article in proceedings – Annual report year: 2012

### Standard

**Numerical Methods for Solution of the Extended Linear Quadratic Control Problem.** / Jørgensen, John Bagterp; Frison, Gianluca; Gade-Nielsen, Nicolai Fog; Dammann, Bernd.

Publication: Research - peer-review › Article in proceedings – Annual report year: 2012

### Harvard

*Nonlinear Model Predictive Control.*vol. 4, International Federation of Automatic Control, pp. 187-193. IFAC Proceedings Volumes (IFAC-PapersOnline) , , 10.3182/20120823-5-NL-3013.00092

### APA

*Nonlinear Model Predictive Control.*(Vol. 4, pp. 187-193). International Federation of Automatic Control. (IFAC Proceedings Volumes (IFAC-PapersOnline) ). 10.3182/20120823-5-NL-3013.00092

### CBE

### MLA

*Nonlinear Model Predictive Control.*International Federation of Automatic Control. 2012. 187-193. (IFAC Proceedings Volumes (IFAC-PapersOnline) ). Available: 10.3182/20120823-5-NL-3013.00092

### Vancouver

### Author

### Bibtex

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### RIS

TY - GEN

T1 - Numerical Methods for Solution of the Extended Linear Quadratic Control Problem

AU - Jørgensen,John Bagterp

AU - Frison,Gianluca

AU - Gade-Nielsen,Nicolai Fog

AU - Dammann,Bernd

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

M3 - Article in proceedings

SN - 978-3-902823-07-6

VL - 4

SP - 187

EP - 193

BT - Nonlinear Model Predictive Control

T2 - Nonlinear Model Predictive Control

PB - International Federation of Automatic Control

ER -