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  Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces

Deisenroth, M., Weissel, F., Ohtsuka, T., & Hanebeck, U. (2007). Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces. In 2007 European Control Conference (ECC) (pp. 3664-3671). Piscataway, NJ, USA: IEEE.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CCC1-F Version Permalink: https://hdl.handle.net/21.11116/0000-0003-E13C-C
Genre: Conference Paper

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https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7068451 (Publisher version)
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 Creators:
Deisenroth, MP1, 2, Author           
Weissel , F, Author
Ohtsuka, T, Author
Hanebeck, UD, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: A novel online-computation approach to optimal control of nonlinear, noise-affected systems with continuous state and control spaces is presented. In the proposed algorithm, system noise is explicitly incorporated into the control decision. This leads to superior results compared to state-of-the-art nonlinear controllers that neglect this influence. The solution of an optimal nonlinear controller for a corresponding deterministic system is employed to find a meaningful state space restriction. This restriction is obtained by means of approximate state prediction using the noisy system equation. Within this constrained state space, an optimal closed-loop solution for a finite decision-making horizon (prediction horizon) is determined within an adaptively restricted optimization space. Interleaving stochastic dynamic programming and value function approximation yields a solution to the considered optimal control problem. The enhanced performance of the proposed discrete-time controller is illustrated by means o
f a scalar example system. Nonlinear model predictive control is applied to address approximate treatment of infinite-horizon problems by the finite-horizon controller.

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 Dates: 2007-07
 Publication Status: Issued
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 Identifiers: BibTex Citekey: 4260
DOI: 10.23919/ECC.2007.7068451
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Title: 9th European Control Conference (ECC 2007)
Place of Event: Kos, Greece
Start-/End Date: 2007-07-02 - 2007-07-05

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Title: 2007 European Control Conference (ECC)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3664 - 3671 Identifier: ISBN: 978-3-9524173-8-6