Detail výsledku
Reliability-Based Control System Optimization in Uncertain Conditions
Hanák Jiří, Ing., Ph.D., UPGM (FIT)
Chudý Peter, doc. Ing., Ph.D., MBA, UPGM (FIT)
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.
Polynomial Chaos Expansion, Cross-Entropy Method, Model Predictive Control
@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"
}