LEARNING CONTROL ALGORITHM FOR NONLINEAR MAPS

Authors
Citation
J. Botina et H. Rabitz, LEARNING CONTROL ALGORITHM FOR NONLINEAR MAPS, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 56(4), 1997, pp. 3854-3858
Citations number
16
Categorie Soggetti
Physycs, Mathematical","Phsycs, Fluid & Plasmas
ISSN journal
1063651X
Volume
56
Issue
4
Year of publication
1997
Pages
3854 - 3858
Database
ISI
SICI code
1063-651X(1997)56:4<3854:LCAFNM>2.0.ZU;2-7
Abstract
A feedback optimal control algorithm is developed for N-dimensional ma ps, which uses learning-based feedback optimal control techniques. The algorithm has two steps: (1) Learn the control of a reference map con taining a stochastic term. (2) Apply the learned control to the labora tory system employing real time feedback. The stochastic component of the learning step is important to provide a close knit family of contr ols to handle laboratory uncertainty and noise. As an example, the for malism is applied to simulated two- and three-dimensional nonlinear la boratory maps in the presence of noise.