The material presented in this document is intended as a comprehensive, implementation-oriented supplement to the experimental optimization framework presented in a companion document. The issues of physical degradation, unknown Lipschitz constants, measurement/estimation noise, gradient estimation, sufficient excitation, and the handling of soft constraints and/or a numerical cost function are all addressed, and a robust, implementable version of the sufficient conditions for feasible-side global convergence is proposed.
@article{arxiv.1406.3997,
title = {Implementation techniques for the SCFO experimental optimization framework},
author = {Gene A. Bunin and Grégory François and Dominique Bonvin},
journal= {arXiv preprint arXiv:1406.3997},
year = {2014}
}