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

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper presents an automated control system tuning approach with emphasis to reliability with respect to vehicle's defined Operational Design Domain (ODD). A joined approach based on Cross-Entropy Method (CEM) and Polynomial Chaos Expansion (PCE) based Kriging meta-model is used to iteratively sample candidate controllers and estimate their failure boundary region with the corresponding probability of failure in the specified ODD. The estimated probability of failure is subsequently used as a heuristic for the sampling distribution update. We show the effectiveness of this approach on multirotor Unmanned Aerial Vehicle (UAV) control system optimization. A dedicated Nonlinear Model Predictive Control (NMPC) scheme augmented by L 1 -adaptive control loop is developed for the quasi-physical model of a UAV and optimized to satisfy the safety requirements imposed by the ODD.

Keywords

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

Authors

NOVÁK, J.; HANÁK, J.; CHUDÝ, P.

Released

2. 8. 2024

Location

Las Vegas

BibTex

@inproceedings{BUT189119,
  author="Jiří {Novák} and Jiří {Hanák} and Peter {Chudý}",
  title="Reliability-Based Control System Optimization in Uncertain Conditions",
  year="2024",
  address="Las Vegas"
}