Semi-receding Horizon Algorithm for “Sufficiently Exciting” MPC with Adaptive Search Step

0438351 - ÚTIA 2015 RIV US eng C - Conference Paper (international conference)
Žáčeková, E. - Pčolka, M. - Čelikovský, Sergej - Šebek, M.
Semi-receding Horizon Algorithm for “Sufficiently Exciting” MPC with Adaptive Search Step.
Proceedings of the 53rd IEEE Conference on Decision and Control (CDC 2014). Los Angeles: IEEE, 2014, s. 4142-4147. Catalog Number: CFP14CDC-CDR. ISBN 978-1-4673-6088-3.
[The 53rd IEEE Conference on Decision and Control (CDC 2014). Los Angeles (US), 15.12.2014-17.12.2014]
R&D Projects: GA ČR GA13-20433S
Institutional support: RVO:67985556
Keywords : Model predictive * Control * Nonlinear systems
Subject RIV: BC - Control Systems Theory
http://library.utia.cas.cz/separaty/2014/TR/celikovsky-0438351.pdf

In this paper, the task of finding an algorithm providing sufficiently excited data within the MPC framework is tackled. Such algorithm is expected to take action only when the re-identification is needed and it shall be used as the “least costly” closed loop identification experiment for MPC. The already existing approach based on maximization of the smallest eigenvalue of the information matrix increase is revised and an adaptation by introducing a semi-receding horizon principle is performed. Further, the optimization algorithm used for the maximization of the provided information is adapted such that the constraints on the maximal allowed control performance deterioration are handled more carefully and are incorporated directly into the process instead of using them just as a termination condition. The effect of the performed adaptations is inspected using a numerical example.
Permanent Link: http://hdl.handle.net/11104/0241783