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Solving equation systems associated with non-linear model predictive control

Ackzell, Erik LU (2015) In Bachelor's Theses in Mathematical Sciences NUMK01 20151
Mathematics (Faculty of Technology) and Numerical Analysis
Abstract
When solving optimization problems associated with non-linear model predictive control, a linear equation system of a specific structure frequently arises. Two different software, CVXGEN and FORCES, developed to generate tailored solvers to specific optimization problems use two different methods when solving this equation system. In this paper, two different sets of software is presented which generate tailored solvers for this equation system using the two different methods. It is found that the solvers which implement the method used in FORCES are faster than the solvers which implement the method used in CVXGEN, as are the generations of the solvers using the FORCES method.

A third software which generate solvers to optimization... (More)
When solving optimization problems associated with non-linear model predictive control, a linear equation system of a specific structure frequently arises. Two different software, CVXGEN and FORCES, developed to generate tailored solvers to specific optimization problems use two different methods when solving this equation system. In this paper, two different sets of software is presented which generate tailored solvers for this equation system using the two different methods. It is found that the solvers which implement the method used in FORCES are faster than the solvers which implement the method used in CVXGEN, as are the generations of the solvers using the FORCES method.

A third software which generate solvers to optimization problems is QPgen, which is now not able to generate solvers for non-linear model predictive control problems. The software presented in this paper is intended to be incorporated in the QPgen software in order to make it able to generate solvers for these problems as well. (Less)
Popular Abstract (Swedish)
När olika fysiska processer ska regleras automatiskt finns det flera metoder att välja bland. En av dessa är så kallad optimeringsbaserad reglering. För att kunna använda optimeringsbaserad reglering krävs att en viss ekvation löses och för att kunna reglera processen snabbt, måste också ekvationen lösas snabbt.

I det här arbetet jämförs två olika metoder att lösa den nämnda ekvationen. De två metoderna förekommer i mjukvarorna CVXGEN och FORCES och vi kan se att metoden som används i FORCES är betydligt snabbare än metoden som används i CVXGEN. Mjukvara för att automatiskt generera program som löser ekvationen med de två metoderna presenteras också och planeras att ingå i ytterligare en annan programvara, QPgen.
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author
Ackzell, Erik LU
supervisor
organization
course
NUMK01 20151
year
type
M2 - Bachelor Degree
subject
keywords
Numerical linear algebra, model predictive control, automatic code generation, CVXGEN, FORCES
publication/series
Bachelor's Theses in Mathematical Sciences
report number
LUNFNA-4007-2015
ISSN
1654-6229
other publication id
2015:K17
language
English
id
8056004
date added to LUP
2015-11-16 12:43:45
date last changed
2015-12-14 13:32:13
@misc{8056004,
  abstract     = {When solving optimization problems associated with non-linear model predictive control, a linear equation system of a specific structure frequently arises. Two different software, CVXGEN and FORCES, developed to generate tailored solvers to specific optimization problems use two different methods when solving this equation system. In this paper, two different sets of software is presented which generate tailored solvers for this equation system using the two different methods. It is found that the solvers which implement the method used in FORCES are faster than the solvers which implement the method used in CVXGEN, as are the generations of the solvers using the FORCES method. 

A third software which generate solvers to optimization problems is QPgen, which is now not able to generate solvers for non-linear model predictive control problems. The software presented in this paper is intended to be incorporated in the QPgen software in order to make it able to generate solvers for these problems as well.},
  author       = {Ackzell, Erik},
  issn         = {1654-6229},
  keyword      = {Numerical linear algebra,model predictive control,automatic code generation,CVXGEN,FORCES},
  language     = {eng},
  note         = {Student Paper},
  series       = {Bachelor's Theses in Mathematical Sciences},
  title        = {Solving equation systems associated with non-linear model predictive control},
  year         = {2015},
}