Conference paper · Journal article
Numerical Methods for Solution of the Extended Linear Quadratic Control Problem
Center for Energy Resources Engineering, Centers, Technical University of Denmark1
Department of Informatics and Mathematical Modeling, Technical University of Denmark2
Scientific Computing, Department of Informatics and Mathematical Modeling, Technical University of Denmark3
Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark5
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.
| Language: | English |
|---|---|
| Publisher: | International Federation of Automatic Control |
| Year: | 2012 |
| Pages: | 187-193 |
| Proceedings: | 4th IFAC Nonlinear Model Predictive Control Conference (NMPC 2012) |
| Series: | Ifac Proceedings Volumes (ifac-papersonline) |
| ISBN: | 3902823070 and 9783902823076 |
| ISSN: | 14746670 |
| Types: | Conference paper and Journal article |
| DOI: | 10.3182/20120823-5-NL-3013.00092 |
| ORCIDs: | Jørgensen, John Bagterp and Dammann, Bernd |
