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Multi-population Genetic Algorithm with the Actor Model Approach to Determine Optimal Braking Torques of the Articulated Vehicle

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Intelligent Computing

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 283))

Abstract

The paper presents an application of message driven optimization to control braking torques on wheels of an articulated vehicle to restore stability during an untripped rollover maneuver. The numerical model of the articulated vehicle and dynamic optimization have been used to calculate appropriate braking torques for each wheel in order to restore stability. The optimization problem requires the equations of motion to be integrated at each optimization step and it is a time-consuming task. Therefore, parallel computing with the use of the Actor Model system has been proposed. The Actor Model has been implemented in the Multi-Population Genetic Algorithm. This paper presents a formulation of Multi-Population Genetic Algorithm with the actor system and results obtained from dynamic optimization.

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Author information

Authors and Affiliations

  1. University of Bielsko-Biala, Willowa 2, Bielsko-Biala, Poland

    Kornel Warwas & Szymon Tengler

Authors
  1. Kornel Warwas
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  2. Szymon Tengler
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Corresponding author

Correspondence to Szymon Tengler .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Warwas, K., Tengler, S. (2022). Multi-population Genetic Algorithm with the Actor Model Approach to Determine Optimal Braking Torques of the Articulated Vehicle. In: Arai, K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-030-80119-9_2

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