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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" }