Implementation of predictive control based on adaptive model to optimize a military vehicle trajectory

Authors

  • Marcelo Andrés Acuña Exército Brasileiro, Instituto Militar de Engenharia. Rio de Janeiro, RJ, Brasil.
  • Gustavo Simão Rodrigues Exército Brasileiro, Instituto Militar de Engenharia. Rio de Janeiro, RJ, Brasil.
  • Elias Dias Rossi Lopes Exército Brasileiro, Instituto Militar de Engenharia. Rio de Janeiro, RJ, Brasil.

Keywords:

DTN, Optimization, Autonomous Vehicle, Deceleration, DLCM, AMPC

Abstract

This article presents a non-linear optimization technique in order to determine the trajectory of a military vehicle during the Double Lane Change Maneuver (DLCM) of the North Atlantic Treaty Organization (NATO). The modeled vehicle is a three-axle truck, the first one with steering wheels. This article also presents the model of lateral dynamics during longitudinal deceleration. The modeling scheme presented in this work takes into account the optimization structure of Adaptive Model Predictive Control (AMPC), composed of the plant with dynamic changes, reference trajectory and plant update, all integrated by the controller, applied to determine the steering wheel angle. The present algorithm is a method widely studied and used in the current design of autonomous vehicles. The method aims to model the driver’s behavior when driving the vehicle during a demanding maneuver.

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Published

2021-01-01

How to Cite

Acuña, M. A., Rodrigues, G. S., & Lopes, E. D. R. . (2021). Implementation of predictive control based on adaptive model to optimize a military vehicle trajectory. Revista Militar De Ciência E Tecnologia, 38(1), 48–53. Retrieved from https://ebrevistas.eb.mil.br/index.php/CT/article/view/8635