Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems

Petros Karamanakos; Tobias Geyer; Ralph Kennel

doi:10.1109/ECCE.2015.7309707

Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems

Petros Karamanakos
, Tobias Geyer
, Ralph Kennel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

43 Citations (Scopus)

16 Downloads (Pure)

Abstract

Search algorithms that reduce the time to solve the direct model predictive control (MPC) problem are proposed in this paper. By allowing for suboptimal solutions, the computational complexity of the underlying optimization problem can be significantly reduced, albeit by sacrificing (to a certain degree) optimality. Two approaches are presented and discussed. The first approach requires quadratic time, making it a very efficient candidate for solving the examined problem. Thanks to the second approach, a preset upper limit on the operations performed in real time is not exceeded, thus guaranteeing realtime termination in all runs. To highlight the effectiveness of the introduced strategies, a variable speed drive system with a three-level voltage source inverter is used as an illustrative example.

Original language	English
Title of host publication	2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015
Publisher	IEEE
Pages	334-341
Number of pages	8
ISBN (Electronic)	9781467371506
DOIs	https://doi.org/10.1109/ECCE.2015.7309707
Publication status	Published - 21 Sept 2015
Publication type	A4 Article in conference proceedings
Event	7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 - Montreal, Canada Duration: 20 Sept 2015 → 24 Sept 2015

Conference

Conference	7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015
Country/Territory	Canada
City	Montreal
Period	20/09/15 → 24/09/15

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/ECCE.2015.7309707

Suboptimal search strategies with bounded computational complexity 2015
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Accepted author manuscript, 281 KB

http://urn.fi/URN:NBN:fi:tuni-202004153261

Cite this

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title = "Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems",

abstract = "Search algorithms that reduce the time to solve the direct model predictive control (MPC) problem are proposed in this paper. By allowing for suboptimal solutions, the computational complexity of the underlying optimization problem can be significantly reduced, albeit by sacrificing (to a certain degree) optimality. Two approaches are presented and discussed. The first approach requires quadratic time, making it a very efficient candidate for solving the examined problem. Thanks to the second approach, a preset upper limit on the operations performed in real time is not exceeded, thus guaranteeing realtime termination in all runs. To highlight the effectiveness of the introduced strategies, a variable speed drive system with a three-level voltage source inverter is used as an illustrative example.",

author = "Petros Karamanakos and Tobias Geyer and Ralph Kennel",

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doi = "10.1109/ECCE.2015.7309707",

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pages = "334--341",

booktitle = "2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015",

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note = "7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 ; Conference date: 20-09-2015 Through 24-09-2015",

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Karamanakos, P, Geyer, T & Kennel, R 2015, Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems. in 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. IEEE, pp. 334-341, 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015, Montreal, Canada, 20/09/15. https://doi.org/10.1109/ECCE.2015.7309707

Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems. / Karamanakos, Petros; Geyer, Tobias; Kennel, Ralph.
2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. IEEE, 2015. p. 334-341.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems

AU - Karamanakos, Petros

AU - Geyer, Tobias

AU - Kennel, Ralph

PY - 2015/9/21

Y1 - 2015/9/21

N2 - Search algorithms that reduce the time to solve the direct model predictive control (MPC) problem are proposed in this paper. By allowing for suboptimal solutions, the computational complexity of the underlying optimization problem can be significantly reduced, albeit by sacrificing (to a certain degree) optimality. Two approaches are presented and discussed. The first approach requires quadratic time, making it a very efficient candidate for solving the examined problem. Thanks to the second approach, a preset upper limit on the operations performed in real time is not exceeded, thus guaranteeing realtime termination in all runs. To highlight the effectiveness of the introduced strategies, a variable speed drive system with a three-level voltage source inverter is used as an illustrative example.

AB - Search algorithms that reduce the time to solve the direct model predictive control (MPC) problem are proposed in this paper. By allowing for suboptimal solutions, the computational complexity of the underlying optimization problem can be significantly reduced, albeit by sacrificing (to a certain degree) optimality. Two approaches are presented and discussed. The first approach requires quadratic time, making it a very efficient candidate for solving the examined problem. Thanks to the second approach, a preset upper limit on the operations performed in real time is not exceeded, thus guaranteeing realtime termination in all runs. To highlight the effectiveness of the introduced strategies, a variable speed drive system with a three-level voltage source inverter is used as an illustrative example.

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M3 - Conference contribution

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BT - 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015

PB - IEEE

T2 - 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015

Y2 - 20 September 2015 through 24 September 2015

ER -

Suboptimal search strategies with bounded computational complexity to solve long-horizon direct model predictive control problems

Abstract

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ASJC Scopus subject areas

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