Stability Analysis of Optimal Adaptive Control using Value Iteration with Approximation Errors
Optimization and Control
2017-10-25 v1 Machine Learning
Systems and Control
Machine Learning
Abstract
Adaptive optimal control using value iteration initiated from a stabilizing control policy is theoretically analyzed in terms of stability of the system during the learning stage without ignoring the effects of approximation errors. This analysis includes the system operated using any single/constant resulting control policy and also using an evolving/time-varying control policy. A feature of the presented results is providing estimations of the \textit{region of attraction} so that if the initial condition is within the region, the whole trajectory will remain inside it and hence, the function approximation results remain valid.
Cite
@article{arxiv.1710.08530,
title = {Stability Analysis of Optimal Adaptive Control using Value Iteration with Approximation Errors},
author = {Ali Heydari},
journal= {arXiv preprint arXiv:1710.08530},
year = {2017}
}
Comments
A part of this paper is based on preliminary results presented in arXiv:1412.5675