Nonlinear Model Predictive Control Approximation: Applications to Truck-Trailer Control System

Suyong Park, Duc Giap Nguyen, Yongsik Jin, Jinrak Park, Dohee Kim, Jeong Soo Eo, Kyoungseok Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we demonstrate the effectiveness of nonlinear model predictive control (NMPC) approximation based on deep neural network (DNN). MPC has been widely adopted in autonomous driving control problems to handle multiple objectives and constraints. We first design the implicit NMPC for the forward and backward motions of a truck-trailer (TT) system, which follows the reference path while maintaining safety between the head truck (HT) and the trailer (TR). However, the computational load in implicit MPC makes it a challenge for real-time implementations. To alleviate the computational burden in implicit NMPC online, an NMPC approximation approach based on DNN is adopted in this study to achieve a parametric function approximation. We conduct a comparative study on the proposed approach and a baseline controller for control performance analysis, and the computational load is evaluated on a hardware-in-the-loop (HIL) experimental system.

Original languageEnglish
Title of host publication2024 24th International Conference on Control, Automation and Systems, ICCAS 2024
PublisherIEEE Computer Society
Pages933-938
Number of pages6
ISBN (Electronic)9788993215380
DOIs
StatePublished - 2024
Event24th International Conference on Control, Automation and Systems, ICCAS 2024 - Jeju, Korea, Republic of
Duration: 29 Oct 20241 Nov 2024

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Conference

Conference24th International Conference on Control, Automation and Systems, ICCAS 2024
Country/TerritoryKorea, Republic of
CityJeju
Period29/10/241/11/24

Keywords

  • control policy approximation
  • Deep neural network
  • hardware-in-the-loop systems
  • nonlinear model predictive control
  • truck-trailer system

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