Forward-looking persistent excitation in model predictive control
Abstract
This work deals with the problem of simultaneous regulation and model parameter estimation in adaptive model predictive control. We propose an adaptive model predictive control and conditions which guarantee a persistently exciting closed loop sequence by only looking forward in time into the receding prediction horizon. Earlier works needed to look backwards and preserve prior regressor data. Instead, we present a procedure for the offline generation of a persistently exciting reference trajectory perturbing the equilibrium. With the new approach we demonstrate exponential convergence of nonlinear systems under the influence of the adaptive model predictive control combined with a recursive least squares identifier with forgetting factor despite bounded noise. The results are, at this stage, local in state and parameter-estimate space.
Cite
@article{arxiv.2004.01625,
title = {Forward-looking persistent excitation in model predictive control},
author = {Sven Brüggemann and Robert R. Bitmead},
journal= {arXiv preprint arXiv:2004.01625},
year = {2021}
}
Comments
11 pages plus references. Extension of IFAC World Congress conference paper through replacement of limiting assumptions and new simulation example