Bayesian Optimization-Based Tunable Explicit MPC on a Pocket-Sized Embedded Platform

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387693" target="_blank" >RIV/68407700:21230/25:00387693 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CDC57313.2025.11312890" target="_blank" >http://dx.doi.org/10.1109/CDC57313.2025.11312890</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CDC57313.2025.11312890" target="_blank" >10.1109/CDC57313.2025.11312890</a>

Result language
angličtina
Original language name
Bayesian Optimization-Based Tunable Explicit MPC on a Pocket-Sized Embedded Platform
Original language description
The paper presents a pocket-sized embedded platform designed for the validation of advanced control methods. The platform is based on the ESP32-S3 microcontroller and is equipped with a miniaturized heat exchange device, making it suitable for temperature control experiments. The platform enables the implementation of a real-time tunable explicit Model Predictive Control (MPC) algorithm, which allows for online tuning of the weighting parameter in the MPC cost function. The paper also introduces a novel application of a method based on Bayesian optimization, which efficiently explores the parameter space to find an optimal performance metric value. The performance metric is a weighted overall parameter of the controller’s performance, in which actuator power consumption and control signal fluctuation are evaluated. Experimental results demonstrate the effectiveness of the proposed approach, while the exploration and exploitation approaches have been tested. Both the explicit MPC controller and the Bayesian optimization method are implemented on the embedded platform, showcasing its capabilities for real-time control applications. The results highlight the potential of the platform for further research and development in advanced control strategies.
Czech name
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Czech description
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Project
<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the IEEE 64th Conference on Decision and Control
ISBN
979-8-3315-2627-6
ISSN
0743-1546
e-ISSN
2576-2370
Number of pages
8
Pages from-to
4663-4670
Publisher name
IEEE
Place of publication
Piscataway
Event location
Rio de Janeiro
Event date
Dec 10, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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