Fast Dynamic Programming

A Numerical Method for Solving Dynamic Programming Problems

Master Thesis (2019)
Author(s)

G.F. Max (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

T Keviczky – Mentor (TU Delft - Team Tamas Keviczky)

Peyman Mohajerin Mohajerin Esfahani – Mentor (TU Delft - Team Tamas Keviczky)

Mohamad Amin Sharifi Sharifi Kolarijani – Graduation committee member (TU Delft - Team Tamas Keviczky)

Alle Jan van der Veen – Graduation committee member (TU Delft - Signal Processing Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2019 Gyula Max
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Gyula Max
Graduation Date
27-11-2019
Awarding Institution
Delft University of Technology
Programme
['Electrical Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

A well-established method for finding the optimal control policy for a given dynamical system is to solve the problem iteratively going from its terminal state "backwards" in time, known as Dynamic Programming Algorithm. For a generic problem with discrete state/action space, the algorithm has computational complexity of O(NM) for N states and M actions. In this thesis, we propose a novel numerical algorithm that approaches this problem in the conjugate domain, using the so-called Legendre-Fenchel Transform. In essence, the proposed approach is analogous to, and was inspired by Fast Fourier Transform, and how it can be beneficial to do computations/analysis in the frequency domain. In particular, this approach allows us to exploit the structure of the problem (e.g., in LQ control) to drastically reduce the computational complexity to O(N+M). Of course, this computational gain comes with a cost of introducing error.

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