Informatics in Control, Automation and Robotics. ICINCO 2021 : Revised Selected Papers

0569998 - ÚTIA 2023 RIV CH eng M - Monography Chapter
Kuklišová Pavelková, Lenka - Belda, Květoslav
Output-Feedback Model Predictive Control Using Set of State Estimates.
Informatics in Control, Automation and Robotics. ICINCO 2021 : Revised Selected Papers. Cham: Springer, 2023 - (Gusikhin, O.; Madani, K.; Nijmeijer, H.), s. 151-162. Lecture Notes in Electrical Engineering, 1006. ISBN 978-3-031-26474-0
Institutional support: RVO:67985556
Keywords : output-feedback control * model predictive control * state estimation * Bayesian methods * robotic system * bounded disturbances
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://library.utia.cas.cz/separaty/2023/AS/kuklisova-0569998.pdf

The paper deals with an algorithm of output-feedback model predictive control (MPC) where the required point state estimate is selected from the set of possible estimates. The involved state estimator is based on an approximate uniform Bayesian filter. In the paper, there are compared conservative mean and progressive composite state estimates. The proposed method is illustrated by the motion control of a specific robotic system.
Permanent Link: https://hdl.handle.net/11104/0341355