Publication detail

Reliability-Based Control System Optimization in Uncertain Conditions

NOVÁK, J. HANÁK, J. CHUDÝ, P.

Original Title

Reliability-Based Control System Optimization in Uncertain Conditions

Type

conference paper

Language

English

Original Abstract

This paper presents an automated control system tuning approach with emphasis on reliability with respect to vehicle's Operational Design Domain (ODD). A joined approach based on Cross-Entropy Method (CEM) and Polynomial Chaos Expansion (PCE) Kriging based surrogate model is used to sample candidate set of system parameters and estimate failure boundary region considering specified ODD. The estimated probability of failure is subsequently used for the sampling distribution update. We show the effectiveness of this approach on number of examples such as control system optimization of Unmanned Aerial vehicle (UAV) modified for aerial grasping. A dedicated Nonlinear Model Predictive Control (NMPC) is developed to solve the coupled control of UAV and robotic arm simultaneously. 

Keywords

Polynomial Chaos Expansion, Cross-Entropy Method, Model Predictive Control

Authors

NOVÁK, J.; HANÁK, J.; CHUDÝ, P.

Released

2. 8. 2024

Publisher

American Institute of Aeronautics and Astronautics

Location

Las Vegas

ISBN

978-1-62410-716-0

Book

AIAA Aviation Forum and ASCEND, 2024

Pages from

1

Pages to

15

Pages count

15

URL

https://arc.aiaa.org/doi/10.2514/6.2024-4571

BibTex

@inproceedings{BUT189119,
  author="Jiří {Novák} and Jiří {Hanák} and Peter {Chudý}",
  title="Reliability-Based Control System Optimization in Uncertain Conditions",
  booktitle="AIAA Aviation Forum and ASCEND, 2024",
  year="2024",
  pages="1--15",
  publisher="American Institute of Aeronautics and Astronautics",
  address="Las Vegas",
  doi="10.2514/6.2024-4571",
  isbn="978-1-62410-716-0",
  url="https://arc.aiaa.org/doi/10.2514/6.2024-4571"
}