Publication Details
Reliability-Based Control System Optimization in Uncertain Conditions
Hanák Jiří, Ing. (DCGM)
Chudý Peter, doc. Ing., Ph.D., MBA (VZ AeroWorks)
Polynomial Chaos Expansion, Cross-Entropy Method, Model Predictive Control
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.
@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"
}