Fast computation of binary search tree for PWA functions representation using intersection classification
| Main Author: | |
|---|---|
| Publication Date: | 2022 |
| Other Authors: | , |
| Format: | Article |
| Language: | eng |
| Source: | Repositório Institucional da Udesc |
| dARK ID: | ark:/33523/001300000b4gh |
| Download full: | https://repositorio.udesc.br/handle/UDESC/2973 |
Summary: | © 2022 Elsevier LtdExplicit Model Predictive Control (eMPC) aims to overcome the runtime computational effort from Model Predictive Control (MPC) by computing offline the overall optimization procedure. The result from eMPC is a Piecewise Affine (PWA) function that defines a relationship between the system state and the optimal control action. To improve the PWA evaluation during runtime, Binary Search Trees (BST) are employed to represent PWA functions, which may be time prohibitive considering the total time to obtain the tree. This note presents a new classification strategy of polyhedral regions with respect to hyperplanes to build BST for PWA functions. The proposed solution is based on the verification of intersection between regions and hyperplanes, resulting in a decrease by almost half in the number of optimization problems, and consequently, in the total time to build the BST, which is the main time-consuming task. The computational time improvement is verified on numerical examples of different sizes, where the same BST is obtained for the original and the proposed classification methods. |
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Fast computation of binary search tree for PWA functions representation using intersection classification© 2022 Elsevier LtdExplicit Model Predictive Control (eMPC) aims to overcome the runtime computational effort from Model Predictive Control (MPC) by computing offline the overall optimization procedure. The result from eMPC is a Piecewise Affine (PWA) function that defines a relationship between the system state and the optimal control action. To improve the PWA evaluation during runtime, Binary Search Trees (BST) are employed to represent PWA functions, which may be time prohibitive considering the total time to obtain the tree. This note presents a new classification strategy of polyhedral regions with respect to hyperplanes to build BST for PWA functions. The proposed solution is based on the verification of intersection between regions and hyperplanes, resulting in a decrease by almost half in the number of optimization problems, and consequently, in the total time to build the BST, which is the main time-consuming task. The computational time improvement is verified on numerical examples of different sizes, where the same BST is obtained for the original and the proposed classification methods.2024-12-05T20:25:51Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0005-109810.1016/j.automatica.2022.110217https://repositorio.udesc.br/handle/UDESC/2973ark:/33523/001300000b4ghAutomatica141Schulze L.*Raffo G.V.Bertol, Douglas Wildgrubeengreponame:Repositório Institucional da Udescinstname:Universidade do Estado de Santa Catarina (UDESC)instacron:UDESCinfo:eu-repo/semantics/openAccess2024-12-07T20:40:22Zoai:repositorio.udesc.br:UDESC/2973Biblioteca Digital de Teses e Dissertaçõeshttps://pergamumweb.udesc.br/biblioteca/index.phpPRIhttps://repositorio-api.udesc.br/server/oai/requestri@udesc.bropendoar:63912024-12-07T20:40:22Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)false |
| dc.title.none.fl_str_mv |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| title |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| spellingShingle |
Fast computation of binary search tree for PWA functions representation using intersection classification Schulze L.* |
| title_short |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| title_full |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| title_fullStr |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| title_full_unstemmed |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| title_sort |
Fast computation of binary search tree for PWA functions representation using intersection classification |
| author |
Schulze L.* |
| author_facet |
Schulze L.* Raffo G.V. Bertol, Douglas Wildgrube |
| author_role |
author |
| author2 |
Raffo G.V. Bertol, Douglas Wildgrube |
| author2_role |
author author |
| dc.contributor.author.fl_str_mv |
Schulze L.* Raffo G.V. Bertol, Douglas Wildgrube |
| description |
© 2022 Elsevier LtdExplicit Model Predictive Control (eMPC) aims to overcome the runtime computational effort from Model Predictive Control (MPC) by computing offline the overall optimization procedure. The result from eMPC is a Piecewise Affine (PWA) function that defines a relationship between the system state and the optimal control action. To improve the PWA evaluation during runtime, Binary Search Trees (BST) are employed to represent PWA functions, which may be time prohibitive considering the total time to obtain the tree. This note presents a new classification strategy of polyhedral regions with respect to hyperplanes to build BST for PWA functions. The proposed solution is based on the verification of intersection between regions and hyperplanes, resulting in a decrease by almost half in the number of optimization problems, and consequently, in the total time to build the BST, which is the main time-consuming task. The computational time improvement is verified on numerical examples of different sizes, where the same BST is obtained for the original and the proposed classification methods. |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022 2024-12-05T20:25:51Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
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publishedVersion |
| dc.identifier.uri.fl_str_mv |
0005-1098 10.1016/j.automatica.2022.110217 https://repositorio.udesc.br/handle/UDESC/2973 |
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ark:/33523/001300000b4gh |
| identifier_str_mv |
0005-1098 10.1016/j.automatica.2022.110217 ark:/33523/001300000b4gh |
| url |
https://repositorio.udesc.br/handle/UDESC/2973 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
Automatica 141 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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reponame:Repositório Institucional da Udesc instname:Universidade do Estado de Santa Catarina (UDESC) instacron:UDESC |
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Universidade do Estado de Santa Catarina (UDESC) |
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UDESC |
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UDESC |
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Repositório Institucional da Udesc |
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Repositório Institucional da Udesc |
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Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC) |
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ri@udesc.br |
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1848168362468704256 |