Numerical methods for constrained optimal control problems

- Hartanto

Research output: ThesisDoctoral Thesis

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Abstract

In this thesis we consider numerical methods for solving state-constrained optimal control problems. There are two main focii in the research, i.e. state- constrained optimal open-loop and feedback control problems. For all cases, we reformulate the constrained optimal control problem to the unconstrained problem through a penalty method. The state-constraints which we discuss here are only in the form of inequalities but for both purely state-constraint and control-state constraint types. For solving state-constrained optimal open-loop control problems, we establish a power penalty method and analyze its convergence. This method is then implemented in MISER 3.3 to do some numerical tests. The results con rm that the method work very well. Furthermore, we use the power penalty method to discuss a sensitivity analysis. On the other hand, for solving state-constrained optimal feedback control problems we construct a new numerical algorithm. The algorithm based on upwind nite di erence scheme is iterated in order to increase the accuracy and speed of computation. In particular to address the curse of dimensionality, a special method for generating grid points in the domain is developed. Numerical experiment shows that the computational speed increases significantly with this modi ed method. Moreover, for further improvement in the accuracy the algorithm can be combined with Richardson Extrapolation Method.
Original languageEnglish
QualificationDoctor of Philosophy
Publication statusUnpublished - 2012

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Numerical methods
Feedback control
Extrapolation
Sensitivity analysis
Experiments

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@phdthesis{28808f6c451c49bd93187094c8260fb6,
title = "Numerical methods for constrained optimal control problems",
abstract = "In this thesis we consider numerical methods for solving state-constrained optimal control problems. There are two main focii in the research, i.e. state- constrained optimal open-loop and feedback control problems. For all cases, we reformulate the constrained optimal control problem to the unconstrained problem through a penalty method. The state-constraints which we discuss here are only in the form of inequalities but for both purely state-constraint and control-state constraint types. For solving state-constrained optimal open-loop control problems, we establish a power penalty method and analyze its convergence. This method is then implemented in MISER 3.3 to do some numerical tests. The results con rm that the method work very well. Furthermore, we use the power penalty method to discuss a sensitivity analysis. On the other hand, for solving state-constrained optimal feedback control problems we construct a new numerical algorithm. The algorithm based on upwind nite di erence scheme is iterated in order to increase the accuracy and speed of computation. In particular to address the curse of dimensionality, a special method for generating grid points in the domain is developed. Numerical experiment shows that the computational speed increases significantly with this modi ed method. Moreover, for further improvement in the accuracy the algorithm can be combined with Richardson Extrapolation Method.",
keywords = "Optimal control, HJB equation, Penalty methods, State constraints",
author = "- Hartanto",
year = "2012",
language = "English",

}

Hartanto 2012, 'Numerical methods for constrained optimal control problems', Doctor of Philosophy.

Numerical methods for constrained optimal control problems. / Hartanto, -.

2012.

Research output: ThesisDoctoral Thesis

TY - THES

T1 - Numerical methods for constrained optimal control problems

AU - Hartanto, -

PY - 2012

Y1 - 2012

N2 - In this thesis we consider numerical methods for solving state-constrained optimal control problems. There are two main focii in the research, i.e. state- constrained optimal open-loop and feedback control problems. For all cases, we reformulate the constrained optimal control problem to the unconstrained problem through a penalty method. The state-constraints which we discuss here are only in the form of inequalities but for both purely state-constraint and control-state constraint types. For solving state-constrained optimal open-loop control problems, we establish a power penalty method and analyze its convergence. This method is then implemented in MISER 3.3 to do some numerical tests. The results con rm that the method work very well. Furthermore, we use the power penalty method to discuss a sensitivity analysis. On the other hand, for solving state-constrained optimal feedback control problems we construct a new numerical algorithm. The algorithm based on upwind nite di erence scheme is iterated in order to increase the accuracy and speed of computation. In particular to address the curse of dimensionality, a special method for generating grid points in the domain is developed. Numerical experiment shows that the computational speed increases significantly with this modi ed method. Moreover, for further improvement in the accuracy the algorithm can be combined with Richardson Extrapolation Method.

AB - In this thesis we consider numerical methods for solving state-constrained optimal control problems. There are two main focii in the research, i.e. state- constrained optimal open-loop and feedback control problems. For all cases, we reformulate the constrained optimal control problem to the unconstrained problem through a penalty method. The state-constraints which we discuss here are only in the form of inequalities but for both purely state-constraint and control-state constraint types. For solving state-constrained optimal open-loop control problems, we establish a power penalty method and analyze its convergence. This method is then implemented in MISER 3.3 to do some numerical tests. The results con rm that the method work very well. Furthermore, we use the power penalty method to discuss a sensitivity analysis. On the other hand, for solving state-constrained optimal feedback control problems we construct a new numerical algorithm. The algorithm based on upwind nite di erence scheme is iterated in order to increase the accuracy and speed of computation. In particular to address the curse of dimensionality, a special method for generating grid points in the domain is developed. Numerical experiment shows that the computational speed increases significantly with this modi ed method. Moreover, for further improvement in the accuracy the algorithm can be combined with Richardson Extrapolation Method.

KW - Optimal control

KW - HJB equation

KW - Penalty methods

KW - State constraints

M3 - Doctoral Thesis

ER -